CA2427606C - A synthetic aperture radar system capable of detecting moving targets - Google Patents
A synthetic aperture radar system capable of detecting moving targets Download PDFInfo
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- CA2427606C CA2427606C CA2427606A CA2427606A CA2427606C CA 2427606 C CA2427606 C CA 2427606C CA 2427606 A CA2427606 A CA 2427606A CA 2427606 A CA2427606 A CA 2427606A CA 2427606 C CA2427606 C CA 2427606C
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/52—Discriminating between fixed and moving objects or between objects moving at different speeds
- G01S13/522—Discriminating between fixed and moving objects or between objects moving at different speeds using transmissions of interrupted pulse modulated waves
- G01S13/524—Discriminating between fixed and moving objects or between objects moving at different speeds using transmissions of interrupted pulse modulated waves based upon the phase or frequency shift resulting from movement of objects, with reference to the transmitted signals, e.g. coherent MTi
- G01S13/5244—Adaptive clutter cancellation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9004—SAR image acquisition techniques
- G01S13/9017—SAR image acquisition techniques with time domain processing of the SAR signals in azimuth
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9029—SAR image post-processing techniques specially adapted for moving target detection within a single SAR image or within multiple SAR images taken at the same time
Abstract
The present invention relates to a Synthetic Aperture Radar (SAR) System capable of detecting moving targets. It comprises a platform which moves over a number of objects, e.g. in the form of a ground surface, and supports radar equipment which reproduces the objects by means of a fast backprojection synthetic aperture technique via at least two antennas without requirement as to directivity or fractional bandwidth. The system comprises a signal-processing device in which the imaging process is divided into three steps which are carried out in a determined order, the steps and the order being formation of sub-aperture beams at one speed, performing clutter suppression, and detection of moving targets.
Description
A Synthetic Aperture Radar System capable of detecting moving targets The present invention relates to a Synthetic Aperture Radar (SAR) System capable of detecting moving targets. The system has no requirement as to directivity or fractional bandwidth. It is therefore possible to use it with an Ultra Wide Band (UWB) SAR system and Wide Beam (WB) transmission and reception.
A UWB-WB SAR at low frequencies will add the capability to detect targets moving in forested areas, and at microwave frequencies it will give the capability of high resolution images of the moving target.
Today there only exists UWB-WB systems at low frequencies, but in time there will be systems also at higher frequencies. The low frequency UWB-WB SAR
system has shown its effectiveness to detect concealed targets. This unique capability is a result of the low frequencies in combination with the relatively high resolution that a UWB-WB SAR sensor gives. This has been successfully demonstrated for instance in the CARABASTM system, Swedish patent 8406007-8 (456 117) and U.S. Pat. No. 4,866,446 and 4,965,582. The resolution in the CARABASTM system is smaller than the center frequency wavelength. To reach this high resolution a very large integration time is needed which demands good motion compensation. Fourier-domain techniques do not adapt to this problem very well, so resolution is reached by time domain backprojection. Fast backprojection techniques (a domain of methods), such as local backprojection (LBP), described i.a. in the Swedish public patent application 9503275-1 and U.S. Pat. No. 5,969,662, and factorized backprojection (FBP), described in "L.M.H. Ulander, H. Hellsten, G. Stenstrom: Synthetic Aperture Radar Processing Using Fast Factorised Backprojection, Proc. of EUSAR 2000, 3rd European Conference on Synthetic Aperture Radar, Germany, pp. 753-756, are approximate and much faster than the global backprojection (GBP).
In UWB-WB SAR only one scatter can appear in the resolution cell and therefore no speckle noise is seen in the images. In particular at low frequencies the radar signal will be stable. Objects that cause radar reflection have a physical size of the wavelength and larger. Low frequency scatters are meters in size, and these large objects do not move between the occasions. As an example, in forests it is not the leaves or branches which cause the reflection, but rather the stable ground-trunk that is the major backscatter contributor.
Detection of moving targets requires maximization of the target signal compared to the clutter signal. In order to filter the strong clutter signal from stationary objects, the displaced-phase-center-antenna (DPCA) method was developed.
This technique needs strict spatial alignment and system stability. In the extension of adaptive antenna technique the space-time adaptive processing (STAP) was found. The STAP is not only adaptive, in the space-time two-dimensional space the clutter spectrum is basically a narrow ridge, so that slow moving targets can be detected.
Clutter suppression by GMTI filtering has in latest years developed in combination with SAR. In a SAR GMTI system the moving target will not only be detected, but also imaged to high resolution in its surroundings. Movement of a target will influence the focusing in the SAR process of the moving target compared to its surroundings. The moving target will be smeared and shifted in location. For SAR with a side-looking narrow beam antenna system these effects are known, and methods for detection of slow moving targets has also been proposed.
In the latest years there has been ongoing development to detect, focus and evaluate velocity components of a moving target in a SAR system. The idea is to use multi-channel antenna arrays to suppress the clutter signal from the stationary objects. The main detection scheme is to compare the likelihood ratio test with a threshold. Later experimental results have shown that SAR GMTI is a strong tool to detect and image moving targets in its surrounding. However, even in these narrow beam microwave systems, compensation in Doppler frequency is needed.
In one known system the test statistics are first filtered for each Doppler frequency, and in another system antenna pattern was compensated in the Doppler domain.
According to one aspect of the present invention, there is provided a Synthetic Aperture Radar (SAR) System capable of detecting moving targets comprising a platform, which moves over a number, which can be very large, of objects, and supports radar equipment which reproduces the objects by means of a fast 2a backprojection synthetic aperture technique via at least two antennas without requirement as to directivity or fractional bandwidth, the radar equipment comprising a signal-processing device performing said backprojection technique, in which the imaging process is divided into three steps which are carried out in a determined order, the steps and the order being formation of sub-aperture beams at one speed, performing clutter suppression based on estimation of the clutter statistics of the sub-aperture beams, and detection of moving targets, wherein the clutter statistics is estimated from the maximum likelihood estimate of the covariance matrix either for surrounding sub-aperture beams connected to surrounding sub images, or for range bins for the sub-aperture beam, after the sub-aperture beam has been divided into such range bins.
Some embodiments of the present invention may provide a solution to the problem of detecting moving targets irrespective of fractional bandwidth and antenna directivity.
The invention will be described below in more detail with reference to the accompanying drawings, in which Figure 1 shows a SAR system according to the invention, Figure 2 defines the co-ordinate system used in this presentation around a SAR system in an aircraft, Figure 3 shows the sub-aperture beam for one sub-aperture over one sub-image, Figure 4 shows the displacement and defocusing of a moving target, Figure 5 shows focusing with relative speed y, using ground speed local beams, Figure 6 shows the geometry of a moving target, Figure 7 shows the image wave vector space, Figure 8 shows one embodiment.of the invention of a detection scheme of moving targets and Figure 9 shows a sub-aperture beam and surrounding sub-aperture beams used to estimate the clutter statistics of the first sub-aperture beam.
The invention uses the approach to combine the fast backprojection techniques with GMTI. The goal is to provide the extreme motion compensation needed in a UWB-WB SAR system and to save computational load both in the SAR processing and the process to focus moving targets at different relative speeds In fast backprojection methods the SAR process has two steps, beam forming and image formation. Because of the linear nature of a GMTI filter and the SAR
process, it is possible to carry out the processing steps in arbitrary order.
The basis for the invention is the appreciation of the fact that by dividing the imaging process into three steps which are carried out in a determined order, the steps and the order being formation of sub-aperture beams at one speed, performing clutter suppression, i.e. GMTI filtering, and detection of moving targets. When necessary in order to get a high enough signal to clutter and noise ratio, the detection of moving targets comprises combining the sub-aperture beams by relative speed.
Fig. 1 shows a SAR system of this type.
The speed normally chosen for the formation of sub-aperture beams is the platform speed or, as seen from the platform, the groundspeed. In the following calcula-tions the speed is chosen in this way. The method is, however, not limited to this. It is possible to choose an arbitrary speed for the initial calculations. A
simple adjustment of the definition of relative speed in the following equations is all that is needed.
The maximum likelihood ratio test is from the sub-aperture beams. The test per-forms clutter suppression in the sub-aperture beams and combines the clutter sup-pressed beams to a test image. The proposed target detection method thus forms sub-aperture beams at one speed, suitably ground speed, perform clutter suppres-sion, and finally combine the sub-aperture beams by relative speed, which is the same as to SAR process a moving target. This means that for all tested relative speeds the same clutter suppressed sub-aperture beams are used. The once computed beams saves computational resources.
The invention will now be described in greater detail. First the SAR
processing algorithm will be discussed. There are many different such algorithms. The choice of algorithm, is dependent on system configuration,,the processing load and the quality of the end product., In UWB-WB SAR systems it has been found that time domain backprojection algorithms are a good choice, due to the capability to handle extreme range migration and motion, compensation needed for the wide antenna aperture. The time domain algorithms originate from the GBP. Because the processing load of GBP is extreme for large images with large apertures, there have been faster time domain algorithms developed. Two such fast backprojection algorithms are LBP and FBP. The LBP is easier to understand and it has therefore been chosen in the following. It is, however, also possible to use other fast back-projection algorithms in connection with the invention.
1 The LBP
Consider Figure 2, A point target at ground position ~0, ilo, 1~0 has for a non-moving target image position x0 = 40 and po - ~o +h2 (to simplify we assume ;0 = 0).
Let g(x,R) be the output from the radar sensor at point (x,R) given by g(xR) - - p(R- (x-xo)2+pol 1 , ( ) (x-x0-Y+ po where' p(R) is the compressed pulse of a point target. The GBP is found from h(x,p)= f g(x', x'-x 2+p2)dx' (2) after post-processing h(x, p) with a ramp-filter in frequency domain.
Consider a target located in a sub-image with center coordinates p, and xC. In LBP
the integral (2) is solved approximately, for this particular sub-image, over M sub-5 apertures with center coordinate xn, cf. Fig. 3. The sub-image and the sub-aperture are chosen so small that the range distance can be approximated as a linear function. The LBP at (x, p) for a point target in (xo, p0) is given by M (xm+L/) A - ~)(x -x + p,, n, C) P~ c' (3) h x .' R +(AX, M=1 I/ L/) . R n, (xm whereR,m= (x0-xm)2+p' ,Ax=(x-x,),Ax'=(x',-xj, andAP=(P-p0).
In LBP the sub-images and sub-aperture size LS are so small that the sub-aperture integral is approximately one dimensional, and will in the following be called sub-aperture beam m+L/
Y,(m,r)= f g x',R0 ,+r+x ,-x Axe cox' = (4) (xm -2 L=) Ro The local beam index 1 is the antenna channel, m the sub-aperture number and r the local distance in the local beam. The LBP can then be rewritten in terms of sub-aperture beams dx(xm -xo)+APPc hl(x,P)=EY1 m, (5) M__1 l Rcm 2 Displacement of moving targets, A moving target will be displaced and unfocused in the SAR image, cf. Fig. 4.
Because the range history is independent of the coordinate system the displace-ment in a UWB-WB SAR system can be found from the distance relation between image coordinates and ground coordinates 72 (x(t) - x0)2 + P02 = (x(t) - (t))2 + Y)2 (t) +h2 (6) Here, y is the relative speed, ~ and i7 are ground coordinates of the moving target, and h is the flight altitude. We assume linear motion of the platform, x(t)=vpt, and the moving target 4(t)=vv(t-to)+o, fi(t)=v,~(t-to)+r~o. The coordinates ~o, 770 and the time to are connected to the minimum range po, and they can easily be found for any linear motion. The distance relation in (6) gives (VP _V4) 2 +V2 (7) VZ
P
V
X. =o - v 17. (8) po = 270 1+ V +h2 (9) VP -V
In the other channels, the moving target appears at positions separated from the first channel. The separation is given by the time difference when the minimum distance occurs in the spatially separated antenna channels. If the separation between the channels antenna phase centers is d1 the separation time At, is found from (6) to be At _ d,(vP-v.) (10) V~-V,, +V, From the separation time the moving target appearance shift in each channel is easily found using (8) and (9).
116xo, = v - v~ fit, {11) V,-V
APO/ v q0 1+ Vq2 At, (12), V17 Po vP _v~
where the approximation vnAt, rto is valid for almost all radar cases. When the approximation is valid the position separation between the channels is linear dependent on the antenna spatial separation.
3 Focusing moving targets To focus the moving target we have to SAR process with correct relative speed.
Above it has been stated that the invention does not us the straight forward method of applying LBP by re-computing the local beams and to repeating the GMTI process. Instead a method to focus SAR images at y using local beams processed for ground speed i.e. y =1 is used.
In LBP (5) we sum local beams over the hyperbola in (xo, po ), see Fig. 5. If the target is moving we can still find the moving target hyperbola in the local beams processed for y =1. However, this needs distance compensation and a sub-image shift, because if the moving target moves fast enough it will appear in different sub-images.
Assume a moving target with minimum range po at x0, see Fig. 5. To find the sub-image and range shift at xm , we compute a point (xo', po '), chosen such that the local beam over a virtual non-moving target at (x0', po ') is the same as for the moving target at (xo, po ). Equal range and range derivative for the moving and non moving target gives VY2(xm -0)2 +po = (xm -4)Z'+po2 (13) (xm-X'0) =y2(Xm-x0) (14) Solving (13) and (14) we get xo' and p0 ' as functions of x,,,, x0, po and r.
The distance shift for a local beam is given by Y 2 2 (15) Lr'õ J = (xm - x0) I p0 - (xm -X0 ) + P0,2 For moving targets with high speed and long integration time, Ar,,, will change so much that the point (xo', po ') changes its location from one sub-image to a neighboring sub-image. When it does, there will be a sub-image shift. The used yl (m,r) is changed to the yl (m,r) connected to that particular sub-image.
4 Moving target detection To detect ground moving targets we have to separate the moving targets from their surroundings. An antenna system with spatial separated antenna channels will have this capability. In a UWB-WB system all channels will contain the same information, except for the moving targets. The moving targets will displace their position in the SAR image compared to the surrounding clutter. They will also change their position between the spatial channels in comparison to the clutter.
The channels measure the same clutter at one and the same spatial position.
With time the moving target will change its position between the channels.
The geometry of the SAR platform and the moving target is given in Figure 6.
The speed of the target is here given by the speed v1 and heading a. As before we assume linear motion. The Doppler angle prelates to non-moving clutter that has the same Doppler as the moving target. The moving target will appear in the sub-aperture connected to op. The angle to the moving~target is given by (p`.
Suppose we want to test if there is a moving target present in an area. In UWB-WB
systems it is a benefit to use sub-aperture beams processed for ground speed for moving target detection. This to compensate frequency and angle dependent mis-match in the system, save processing load and reduce data complexity.
The illuminated area is divided into sub-images that are connected to sub-aperture beams y1(m,r). If a moving target is present, the. local beams consist of a moving target z, m,r), clutter and white noise independent of direction n(r). The local beam y, (m, r) under the two hypotheses, Ho no target present and, Hl target present are Ho: .v (in,r)= ai (m, r)* V(m,r)+n1(r) (16) Hl: y1(n1,r)= al(m,r)*z1(m,r)+ 17 1 ( , ) i( ) 1( ) () where * is convolution, al (r) is the system influence on the clutter, and al (r) similarly for the target. These functions differ because of the different origin direc-tions of the target and the clutter in' the sub-aperture beam, see section 3 above.
The measurements in the radar system will be sampled signals so we will in the following use the sampled sub-aperture beam y, (m,rõ).
Range or time domain filtering in UWB systems puts very high demands on the system calibration. Experience from wide band jammer suppression in a UWB
A UWB-WB SAR at low frequencies will add the capability to detect targets moving in forested areas, and at microwave frequencies it will give the capability of high resolution images of the moving target.
Today there only exists UWB-WB systems at low frequencies, but in time there will be systems also at higher frequencies. The low frequency UWB-WB SAR
system has shown its effectiveness to detect concealed targets. This unique capability is a result of the low frequencies in combination with the relatively high resolution that a UWB-WB SAR sensor gives. This has been successfully demonstrated for instance in the CARABASTM system, Swedish patent 8406007-8 (456 117) and U.S. Pat. No. 4,866,446 and 4,965,582. The resolution in the CARABASTM system is smaller than the center frequency wavelength. To reach this high resolution a very large integration time is needed which demands good motion compensation. Fourier-domain techniques do not adapt to this problem very well, so resolution is reached by time domain backprojection. Fast backprojection techniques (a domain of methods), such as local backprojection (LBP), described i.a. in the Swedish public patent application 9503275-1 and U.S. Pat. No. 5,969,662, and factorized backprojection (FBP), described in "L.M.H. Ulander, H. Hellsten, G. Stenstrom: Synthetic Aperture Radar Processing Using Fast Factorised Backprojection, Proc. of EUSAR 2000, 3rd European Conference on Synthetic Aperture Radar, Germany, pp. 753-756, are approximate and much faster than the global backprojection (GBP).
In UWB-WB SAR only one scatter can appear in the resolution cell and therefore no speckle noise is seen in the images. In particular at low frequencies the radar signal will be stable. Objects that cause radar reflection have a physical size of the wavelength and larger. Low frequency scatters are meters in size, and these large objects do not move between the occasions. As an example, in forests it is not the leaves or branches which cause the reflection, but rather the stable ground-trunk that is the major backscatter contributor.
Detection of moving targets requires maximization of the target signal compared to the clutter signal. In order to filter the strong clutter signal from stationary objects, the displaced-phase-center-antenna (DPCA) method was developed.
This technique needs strict spatial alignment and system stability. In the extension of adaptive antenna technique the space-time adaptive processing (STAP) was found. The STAP is not only adaptive, in the space-time two-dimensional space the clutter spectrum is basically a narrow ridge, so that slow moving targets can be detected.
Clutter suppression by GMTI filtering has in latest years developed in combination with SAR. In a SAR GMTI system the moving target will not only be detected, but also imaged to high resolution in its surroundings. Movement of a target will influence the focusing in the SAR process of the moving target compared to its surroundings. The moving target will be smeared and shifted in location. For SAR with a side-looking narrow beam antenna system these effects are known, and methods for detection of slow moving targets has also been proposed.
In the latest years there has been ongoing development to detect, focus and evaluate velocity components of a moving target in a SAR system. The idea is to use multi-channel antenna arrays to suppress the clutter signal from the stationary objects. The main detection scheme is to compare the likelihood ratio test with a threshold. Later experimental results have shown that SAR GMTI is a strong tool to detect and image moving targets in its surrounding. However, even in these narrow beam microwave systems, compensation in Doppler frequency is needed.
In one known system the test statistics are first filtered for each Doppler frequency, and in another system antenna pattern was compensated in the Doppler domain.
According to one aspect of the present invention, there is provided a Synthetic Aperture Radar (SAR) System capable of detecting moving targets comprising a platform, which moves over a number, which can be very large, of objects, and supports radar equipment which reproduces the objects by means of a fast 2a backprojection synthetic aperture technique via at least two antennas without requirement as to directivity or fractional bandwidth, the radar equipment comprising a signal-processing device performing said backprojection technique, in which the imaging process is divided into three steps which are carried out in a determined order, the steps and the order being formation of sub-aperture beams at one speed, performing clutter suppression based on estimation of the clutter statistics of the sub-aperture beams, and detection of moving targets, wherein the clutter statistics is estimated from the maximum likelihood estimate of the covariance matrix either for surrounding sub-aperture beams connected to surrounding sub images, or for range bins for the sub-aperture beam, after the sub-aperture beam has been divided into such range bins.
Some embodiments of the present invention may provide a solution to the problem of detecting moving targets irrespective of fractional bandwidth and antenna directivity.
The invention will be described below in more detail with reference to the accompanying drawings, in which Figure 1 shows a SAR system according to the invention, Figure 2 defines the co-ordinate system used in this presentation around a SAR system in an aircraft, Figure 3 shows the sub-aperture beam for one sub-aperture over one sub-image, Figure 4 shows the displacement and defocusing of a moving target, Figure 5 shows focusing with relative speed y, using ground speed local beams, Figure 6 shows the geometry of a moving target, Figure 7 shows the image wave vector space, Figure 8 shows one embodiment.of the invention of a detection scheme of moving targets and Figure 9 shows a sub-aperture beam and surrounding sub-aperture beams used to estimate the clutter statistics of the first sub-aperture beam.
The invention uses the approach to combine the fast backprojection techniques with GMTI. The goal is to provide the extreme motion compensation needed in a UWB-WB SAR system and to save computational load both in the SAR processing and the process to focus moving targets at different relative speeds In fast backprojection methods the SAR process has two steps, beam forming and image formation. Because of the linear nature of a GMTI filter and the SAR
process, it is possible to carry out the processing steps in arbitrary order.
The basis for the invention is the appreciation of the fact that by dividing the imaging process into three steps which are carried out in a determined order, the steps and the order being formation of sub-aperture beams at one speed, performing clutter suppression, i.e. GMTI filtering, and detection of moving targets. When necessary in order to get a high enough signal to clutter and noise ratio, the detection of moving targets comprises combining the sub-aperture beams by relative speed.
Fig. 1 shows a SAR system of this type.
The speed normally chosen for the formation of sub-aperture beams is the platform speed or, as seen from the platform, the groundspeed. In the following calcula-tions the speed is chosen in this way. The method is, however, not limited to this. It is possible to choose an arbitrary speed for the initial calculations. A
simple adjustment of the definition of relative speed in the following equations is all that is needed.
The maximum likelihood ratio test is from the sub-aperture beams. The test per-forms clutter suppression in the sub-aperture beams and combines the clutter sup-pressed beams to a test image. The proposed target detection method thus forms sub-aperture beams at one speed, suitably ground speed, perform clutter suppres-sion, and finally combine the sub-aperture beams by relative speed, which is the same as to SAR process a moving target. This means that for all tested relative speeds the same clutter suppressed sub-aperture beams are used. The once computed beams saves computational resources.
The invention will now be described in greater detail. First the SAR
processing algorithm will be discussed. There are many different such algorithms. The choice of algorithm, is dependent on system configuration,,the processing load and the quality of the end product., In UWB-WB SAR systems it has been found that time domain backprojection algorithms are a good choice, due to the capability to handle extreme range migration and motion, compensation needed for the wide antenna aperture. The time domain algorithms originate from the GBP. Because the processing load of GBP is extreme for large images with large apertures, there have been faster time domain algorithms developed. Two such fast backprojection algorithms are LBP and FBP. The LBP is easier to understand and it has therefore been chosen in the following. It is, however, also possible to use other fast back-projection algorithms in connection with the invention.
1 The LBP
Consider Figure 2, A point target at ground position ~0, ilo, 1~0 has for a non-moving target image position x0 = 40 and po - ~o +h2 (to simplify we assume ;0 = 0).
Let g(x,R) be the output from the radar sensor at point (x,R) given by g(xR) - - p(R- (x-xo)2+pol 1 , ( ) (x-x0-Y+ po where' p(R) is the compressed pulse of a point target. The GBP is found from h(x,p)= f g(x', x'-x 2+p2)dx' (2) after post-processing h(x, p) with a ramp-filter in frequency domain.
Consider a target located in a sub-image with center coordinates p, and xC. In LBP
the integral (2) is solved approximately, for this particular sub-image, over M sub-5 apertures with center coordinate xn, cf. Fig. 3. The sub-image and the sub-aperture are chosen so small that the range distance can be approximated as a linear function. The LBP at (x, p) for a point target in (xo, p0) is given by M (xm+L/) A - ~)(x -x + p,, n, C) P~ c' (3) h x .' R +(AX, M=1 I/ L/) . R n, (xm whereR,m= (x0-xm)2+p' ,Ax=(x-x,),Ax'=(x',-xj, andAP=(P-p0).
In LBP the sub-images and sub-aperture size LS are so small that the sub-aperture integral is approximately one dimensional, and will in the following be called sub-aperture beam m+L/
Y,(m,r)= f g x',R0 ,+r+x ,-x Axe cox' = (4) (xm -2 L=) Ro The local beam index 1 is the antenna channel, m the sub-aperture number and r the local distance in the local beam. The LBP can then be rewritten in terms of sub-aperture beams dx(xm -xo)+APPc hl(x,P)=EY1 m, (5) M__1 l Rcm 2 Displacement of moving targets, A moving target will be displaced and unfocused in the SAR image, cf. Fig. 4.
Because the range history is independent of the coordinate system the displace-ment in a UWB-WB SAR system can be found from the distance relation between image coordinates and ground coordinates 72 (x(t) - x0)2 + P02 = (x(t) - (t))2 + Y)2 (t) +h2 (6) Here, y is the relative speed, ~ and i7 are ground coordinates of the moving target, and h is the flight altitude. We assume linear motion of the platform, x(t)=vpt, and the moving target 4(t)=vv(t-to)+o, fi(t)=v,~(t-to)+r~o. The coordinates ~o, 770 and the time to are connected to the minimum range po, and they can easily be found for any linear motion. The distance relation in (6) gives (VP _V4) 2 +V2 (7) VZ
P
V
X. =o - v 17. (8) po = 270 1+ V +h2 (9) VP -V
In the other channels, the moving target appears at positions separated from the first channel. The separation is given by the time difference when the minimum distance occurs in the spatially separated antenna channels. If the separation between the channels antenna phase centers is d1 the separation time At, is found from (6) to be At _ d,(vP-v.) (10) V~-V,, +V, From the separation time the moving target appearance shift in each channel is easily found using (8) and (9).
116xo, = v - v~ fit, {11) V,-V
APO/ v q0 1+ Vq2 At, (12), V17 Po vP _v~
where the approximation vnAt, rto is valid for almost all radar cases. When the approximation is valid the position separation between the channels is linear dependent on the antenna spatial separation.
3 Focusing moving targets To focus the moving target we have to SAR process with correct relative speed.
Above it has been stated that the invention does not us the straight forward method of applying LBP by re-computing the local beams and to repeating the GMTI process. Instead a method to focus SAR images at y using local beams processed for ground speed i.e. y =1 is used.
In LBP (5) we sum local beams over the hyperbola in (xo, po ), see Fig. 5. If the target is moving we can still find the moving target hyperbola in the local beams processed for y =1. However, this needs distance compensation and a sub-image shift, because if the moving target moves fast enough it will appear in different sub-images.
Assume a moving target with minimum range po at x0, see Fig. 5. To find the sub-image and range shift at xm , we compute a point (xo', po '), chosen such that the local beam over a virtual non-moving target at (x0', po ') is the same as for the moving target at (xo, po ). Equal range and range derivative for the moving and non moving target gives VY2(xm -0)2 +po = (xm -4)Z'+po2 (13) (xm-X'0) =y2(Xm-x0) (14) Solving (13) and (14) we get xo' and p0 ' as functions of x,,,, x0, po and r.
The distance shift for a local beam is given by Y 2 2 (15) Lr'õ J = (xm - x0) I p0 - (xm -X0 ) + P0,2 For moving targets with high speed and long integration time, Ar,,, will change so much that the point (xo', po ') changes its location from one sub-image to a neighboring sub-image. When it does, there will be a sub-image shift. The used yl (m,r) is changed to the yl (m,r) connected to that particular sub-image.
4 Moving target detection To detect ground moving targets we have to separate the moving targets from their surroundings. An antenna system with spatial separated antenna channels will have this capability. In a UWB-WB system all channels will contain the same information, except for the moving targets. The moving targets will displace their position in the SAR image compared to the surrounding clutter. They will also change their position between the spatial channels in comparison to the clutter.
The channels measure the same clutter at one and the same spatial position.
With time the moving target will change its position between the channels.
The geometry of the SAR platform and the moving target is given in Figure 6.
The speed of the target is here given by the speed v1 and heading a. As before we assume linear motion. The Doppler angle prelates to non-moving clutter that has the same Doppler as the moving target. The moving target will appear in the sub-aperture connected to op. The angle to the moving~target is given by (p`.
Suppose we want to test if there is a moving target present in an area. In UWB-WB
systems it is a benefit to use sub-aperture beams processed for ground speed for moving target detection. This to compensate frequency and angle dependent mis-match in the system, save processing load and reduce data complexity.
The illuminated area is divided into sub-images that are connected to sub-aperture beams y1(m,r). If a moving target is present, the. local beams consist of a moving target z, m,r), clutter and white noise independent of direction n(r). The local beam y, (m, r) under the two hypotheses, Ho no target present and, Hl target present are Ho: .v (in,r)= ai (m, r)* V(m,r)+n1(r) (16) Hl: y1(n1,r)= al(m,r)*z1(m,r)+ 17 1 ( , ) i( ) 1( ) () where * is convolution, al (r) is the system influence on the clutter, and al (r) similarly for the target. These functions differ because of the different origin direc-tions of the target and the clutter in' the sub-aperture beam, see section 3 above.
The measurements in the radar system will be sampled signals so we will in the following use the sampled sub-aperture beam y, (m,rõ).
Range or time domain filtering in UWB systems puts very high demands on the system calibration. Experience from wide band jammer suppression in a UWB
system indicates that the filtering should be done in frequency domain. Let the system have L antenna channels. The received signal under the two hypotheses H0 and HI in frequency domain are Ho: y1(k)=Al (k)rjt(k)+nl(k) (18) H1: YI (k)= Ai (kk ~~~)e~~r(k~(z-1)o)k (19) +AI k)1i(k)+iit(k) where k is the wave vector dependent on the wave number k and index ni (dependent on Doppler angle cp), A denotes the movement of the moving target between the spatial channels, Al (k) is the frequency function of the system in the clutter direction, A,#) is the frequency function of the system in the target direc-tion, s(k) is the amplitude and q$(k) is the phase of the target scattering.
Working with sub-aperture beams it is preferred to use a polar coordinate system wave vector domain, where k is expressed as k and 0 (the same angle as q in means of stationary phase). The wave number index in radial direction is n and in the angle direction m. Wave number domain of the sub aperture beams connected to one sub image is seen in Fig. 7.
The measurement vector in wave vector domain for all channels L and all sampled frequency transformed sub aperture beams is Yj(k1,V1,9211 Y2(k1,(P1,co'1) _ YL(kj~Vi1 P11) Y = Y1(k2,cp1,c'1) =A+k +n (20) YL (kN, V1, V'1) YL(kN3VM,VIM
) where and n is the clutter and noise vector, respectively. Let us assume that AI (k)= AI (k)=1 over the used wave numbers. The signal vector is given by e.7~(k1,c0'1)s(k1 , '0'1-Jktr(~P
e1O(k,,p'1)s(k q,' -Jkt(r(So' )+d(costy-cosp'1)) 1, 1 ei&1,V1)s(k, V b-1k1(r(~1} (L-l~d(cosrq-aoscp't~~
A. _ e. O(k2,c1)s(k2 ~P'11 Jk2r(q'1) (21) e.lO(kN,V'1)s(kN )-JkN(r(~t)+(L-1)d(cos{y-Cos q'1)) e1O(kN,co'M) s1kN , 4#m 1õ-JkN(r(q'M)+(L-1)d(cos ,-cos /MSP M)) The moving target will in the sub-aperture beamsperform a local range walk given by r(~p,;,). The walk is dependent on the range migration, which depends on the 5 relative speed (7).
To test if there is a target present we use the likelihood ratio test. The likelihood ratio is denoted A = P YIH' (22) P YIHO
The probability density function (pdf)'of the noise n1(rõ) is Gaussian. The resolu-tion in each radar output is poor compared to the center wavelength, and for that reason the resolution cell contains many scatters. It is then appropriate to assume i7 (m, r;,) pdf as Gaussian . The transformation from range to frequency domain of a sequence is a summation, and a summation of Gaussian variables is Gaussian.
The pdf of the clutter and noise n is believed to be Gaussian. Then under HO:
-pxC-1p P(Y jH) t e (23) ~ (2~~ ICI
and under HI:
... N
P(YI Hl) = 1 e-~r A) A (24) (2k)w jcj where C is the covariance matrix of E[(~ +nR~ +n)H (25) If a moving point target is assumed, we can simplify the measurement signal. A
point target reflects with the same amplitude so and the same phase 0o for all directions and over the entire frequency band. The amplitude of the measured signal will only dependent on the distance to the sub-aperture center R,,,,.
The phase 0o is random and distributed uniformly between 0 and 27C . Under the point target approximation the signal vector can be expressed as A=soejo A (26) A is the steering vector given by ejkirl Rc1 2 e jkl (rl+d (cos q11-cos (p't )) Rol e jk, (r,+(L-1)d (cos (,1-cos V',)) Rcl 2 A = ejk2rl (27) z Rcl e jkr, (r,+d (cos p1-cos p',)) Rc2 e jkN(r 1+(L-1)d (cos V,,-cos 'P'M )) where the distance r,,, = r(gpn,) is the local distance. Since 0o is random the likeli-hood ratio test is given by EO[A(Y)]= f A(YlO0) 2~c2 (28) The test variable is H, 12HJ~_,f12(29) HO
The covariance matrix is dependent on the clutter covariance and the noise.
The clutter noise and the receiver noise can be considered as independent C = EIYYH ]= Ekrl H+E[nnH (30) The receiver noise samples nt (rn) are independent both in rõ and 1. The clutter signal r1(m, r;,) is dependent in 1, independent in m and r,,. The sub-aperture beams are formed by non overlapping samples, which are independent (independ-ent looks). The Fourier transformation will cause dependency on k both for r1 and ii. However these dependencies are probable weak so we assume the samples to be independent in k. The covariance will simplify to C11 0 0 ' 0 ... 0 0 C21 === 0 0 === 0 C= 0 0 CNI 0 === 0 (31) 0 0 0 C12 .=. 0 0 0 0 0 0 === CNM
where the diagonal matrixes C,,. = ELrlnmrlnmH ]+ E1 ,,n, 2nmH ], (32) where the clutter r1nn, and the noise fin, is indexed the same as the measurement vector Yõn, which, for a particular frequency and direction, is ~~ !n Pn'11 kõ, Yo, ,Y m) = Y2(kn, nm (33) !!nn i YL(kn,Y m,~m) The likelihood ratio test can then be reduced to _ H -1Y ti2 = M N ~1 1H. 1 ??M _ nm (2 Ht 34) C I A
ni=l n=1 Ho where the steering end up as a vector dependent on m and n.
e--Arm e-jkõd(cos9,,,-cosq'm a jknr" (35) ee~
d_rrn: 2 R R 2 "rrm `~
cm cm e- jkn (L-1 )d (cos q,,, -cos G'm The detector filter variable will be M N
x 1 F(A,a)_ JACnmYnm (36) m=1 n=1 and the expectation value will be m N _ E[F(A, a)] = s0ej~o l~ ` AmnCmn`4nrn (37) m=I Ln=11 What. is the expectation value given in (37)? To illustrate this we form the product, which is equal to the expectation value when rõ', = rm S of 0 ejknr.Ax C-1 e-jknr (38) 0 2 nm nn: nm M=1 Rcnr n=1 Because the covariance matrix Cõ,;, is Hermitian and positive definite the product nrCnn1 -1 r`4nnr = (A nrCnnrAnnrl In case of maximum likelihood we match the distance walk between the sub-apertures. To match the distance walk with a phase shift in frequency is a SAR process. According to section 3 above, r, is connected to the relative speed r. To test we therefore use the methods developed in sections 1-3.
To illustrate we assume the signal to be so strong that the noise can be neglected, ,n and we write let Fn,, = A nCnIn =
A
N
Am, rm') _ I ejkõ n,Fnma-'knr- = g'(rm - rm) (39) n=1 where N
g'(f m) - Fnnre lknrm (40) n=1 The test then is H, (41) Ho where h, x M , na ~(xm-xa)+~ppa -A1 (42) (gyp}=ly m m=1 Ram One embodiment of a detection scheme for moving target is shown in Fig. 8. The system is built of two or more channels, and is, in this case, illustrated for three, 1,2,3.
First sub-aperture, beams are formed for each channel.. Normally they. are formed for ground speed, as discussed above and shown in Fig. 3: The sub-images are then related to a specific area on the ground. The proposed method is adaptive by using measured data to estimate the clutter statistics.
A first method to estimate the clutter statistics of the sub-aperture beam for a sub-image with the point (xo,po) is to use the surrounding sub-aperture beams con-nected to the surrounding sub images, cf. Fig. 9. The clutter statistics is in this case estimated from the maximum likelihood estimate of the covariance matrix CP =EYpfpH,~ i7pYpH (43) g P=1 where p is the index of the sub aperture connected to the surrounding sub-image p.
The algorithm will automatically compensate for the differences between the antenna channels. The covariance matrix C is inverted C-1 and used, together with the steering vector 2, in (29) or (34). In this step it is possible to detect moving targets. To increase the detection possibility the clutter suppressed signal are combined for different relative speeds y. In the formed images moving targets with different relative speed can be found and imaged.
There is a second method to estimate the clutter statistics to be used in connection with the method in Fig. 8. The sub-aperture beam for a sub-image with the point (xo,po) is divided into range bins. A range bin is a range interval having a number of range samples. Under the assumption that the clutter signal is much stronger than the target signal, the covariance is estimated between the channels by the maximum likelihood estimate of the covariance, which means the use of equation (43), withp, in this case, being the index for the sub-aperture bins.
Working with sub-aperture beams it is preferred to use a polar coordinate system wave vector domain, where k is expressed as k and 0 (the same angle as q in means of stationary phase). The wave number index in radial direction is n and in the angle direction m. Wave number domain of the sub aperture beams connected to one sub image is seen in Fig. 7.
The measurement vector in wave vector domain for all channels L and all sampled frequency transformed sub aperture beams is Yj(k1,V1,9211 Y2(k1,(P1,co'1) _ YL(kj~Vi1 P11) Y = Y1(k2,cp1,c'1) =A+k +n (20) YL (kN, V1, V'1) YL(kN3VM,VIM
) where and n is the clutter and noise vector, respectively. Let us assume that AI (k)= AI (k)=1 over the used wave numbers. The signal vector is given by e.7~(k1,c0'1)s(k1 , '0'1-Jktr(~P
e1O(k,,p'1)s(k q,' -Jkt(r(So' )+d(costy-cosp'1)) 1, 1 ei&1,V1)s(k, V b-1k1(r(~1} (L-l~d(cosrq-aoscp't~~
A. _ e. O(k2,c1)s(k2 ~P'11 Jk2r(q'1) (21) e.lO(kN,V'1)s(kN )-JkN(r(~t)+(L-1)d(cos{y-Cos q'1)) e1O(kN,co'M) s1kN , 4#m 1õ-JkN(r(q'M)+(L-1)d(cos ,-cos /MSP M)) The moving target will in the sub-aperture beamsperform a local range walk given by r(~p,;,). The walk is dependent on the range migration, which depends on the 5 relative speed (7).
To test if there is a target present we use the likelihood ratio test. The likelihood ratio is denoted A = P YIH' (22) P YIHO
The probability density function (pdf)'of the noise n1(rõ) is Gaussian. The resolu-tion in each radar output is poor compared to the center wavelength, and for that reason the resolution cell contains many scatters. It is then appropriate to assume i7 (m, r;,) pdf as Gaussian . The transformation from range to frequency domain of a sequence is a summation, and a summation of Gaussian variables is Gaussian.
The pdf of the clutter and noise n is believed to be Gaussian. Then under HO:
-pxC-1p P(Y jH) t e (23) ~ (2~~ ICI
and under HI:
... N
P(YI Hl) = 1 e-~r A) A (24) (2k)w jcj where C is the covariance matrix of E[(~ +nR~ +n)H (25) If a moving point target is assumed, we can simplify the measurement signal. A
point target reflects with the same amplitude so and the same phase 0o for all directions and over the entire frequency band. The amplitude of the measured signal will only dependent on the distance to the sub-aperture center R,,,,.
The phase 0o is random and distributed uniformly between 0 and 27C . Under the point target approximation the signal vector can be expressed as A=soejo A (26) A is the steering vector given by ejkirl Rc1 2 e jkl (rl+d (cos q11-cos (p't )) Rol e jk, (r,+(L-1)d (cos (,1-cos V',)) Rcl 2 A = ejk2rl (27) z Rcl e jkr, (r,+d (cos p1-cos p',)) Rc2 e jkN(r 1+(L-1)d (cos V,,-cos 'P'M )) where the distance r,,, = r(gpn,) is the local distance. Since 0o is random the likeli-hood ratio test is given by EO[A(Y)]= f A(YlO0) 2~c2 (28) The test variable is H, 12HJ~_,f12(29) HO
The covariance matrix is dependent on the clutter covariance and the noise.
The clutter noise and the receiver noise can be considered as independent C = EIYYH ]= Ekrl H+E[nnH (30) The receiver noise samples nt (rn) are independent both in rõ and 1. The clutter signal r1(m, r;,) is dependent in 1, independent in m and r,,. The sub-aperture beams are formed by non overlapping samples, which are independent (independ-ent looks). The Fourier transformation will cause dependency on k both for r1 and ii. However these dependencies are probable weak so we assume the samples to be independent in k. The covariance will simplify to C11 0 0 ' 0 ... 0 0 C21 === 0 0 === 0 C= 0 0 CNI 0 === 0 (31) 0 0 0 C12 .=. 0 0 0 0 0 0 === CNM
where the diagonal matrixes C,,. = ELrlnmrlnmH ]+ E1 ,,n, 2nmH ], (32) where the clutter r1nn, and the noise fin, is indexed the same as the measurement vector Yõn, which, for a particular frequency and direction, is ~~ !n Pn'11 kõ, Yo, ,Y m) = Y2(kn, nm (33) !!nn i YL(kn,Y m,~m) The likelihood ratio test can then be reduced to _ H -1Y ti2 = M N ~1 1H. 1 ??M _ nm (2 Ht 34) C I A
ni=l n=1 Ho where the steering end up as a vector dependent on m and n.
e--Arm e-jkõd(cos9,,,-cosq'm a jknr" (35) ee~
d_rrn: 2 R R 2 "rrm `~
cm cm e- jkn (L-1 )d (cos q,,, -cos G'm The detector filter variable will be M N
x 1 F(A,a)_ JACnmYnm (36) m=1 n=1 and the expectation value will be m N _ E[F(A, a)] = s0ej~o l~ ` AmnCmn`4nrn (37) m=I Ln=11 What. is the expectation value given in (37)? To illustrate this we form the product, which is equal to the expectation value when rõ', = rm S of 0 ejknr.Ax C-1 e-jknr (38) 0 2 nm nn: nm M=1 Rcnr n=1 Because the covariance matrix Cõ,;, is Hermitian and positive definite the product nrCnn1 -1 r`4nnr = (A nrCnnrAnnrl In case of maximum likelihood we match the distance walk between the sub-apertures. To match the distance walk with a phase shift in frequency is a SAR process. According to section 3 above, r, is connected to the relative speed r. To test we therefore use the methods developed in sections 1-3.
To illustrate we assume the signal to be so strong that the noise can be neglected, ,n and we write let Fn,, = A nCnIn =
A
N
Am, rm') _ I ejkõ n,Fnma-'knr- = g'(rm - rm) (39) n=1 where N
g'(f m) - Fnnre lknrm (40) n=1 The test then is H, (41) Ho where h, x M , na ~(xm-xa)+~ppa -A1 (42) (gyp}=ly m m=1 Ram One embodiment of a detection scheme for moving target is shown in Fig. 8. The system is built of two or more channels, and is, in this case, illustrated for three, 1,2,3.
First sub-aperture, beams are formed for each channel.. Normally they. are formed for ground speed, as discussed above and shown in Fig. 3: The sub-images are then related to a specific area on the ground. The proposed method is adaptive by using measured data to estimate the clutter statistics.
A first method to estimate the clutter statistics of the sub-aperture beam for a sub-image with the point (xo,po) is to use the surrounding sub-aperture beams con-nected to the surrounding sub images, cf. Fig. 9. The clutter statistics is in this case estimated from the maximum likelihood estimate of the covariance matrix CP =EYpfpH,~ i7pYpH (43) g P=1 where p is the index of the sub aperture connected to the surrounding sub-image p.
The algorithm will automatically compensate for the differences between the antenna channels. The covariance matrix C is inverted C-1 and used, together with the steering vector 2, in (29) or (34). In this step it is possible to detect moving targets. To increase the detection possibility the clutter suppressed signal are combined for different relative speeds y. In the formed images moving targets with different relative speed can be found and imaged.
There is a second method to estimate the clutter statistics to be used in connection with the method in Fig. 8. The sub-aperture beam for a sub-image with the point (xo,po) is divided into range bins. A range bin is a range interval having a number of range samples. Under the assumption that the clutter signal is much stronger than the target signal, the covariance is estimated between the channels by the maximum likelihood estimate of the covariance, which means the use of equation (43), withp, in this case, being the index for the sub-aperture bins.
Claims (5)
1. A Synthetic Aperture Radar (SAR) System capable of detecting moving targets comprising a platform, which moves over a number, which can be very large, of objects, and supports radar equipment which reproduces the objects by means of a fast backprojection synthetic aperture technique via at least two antennas without requirement as to directivity or fractional bandwidth, the radar equipment comprising a signal-processing device performing said backprojection technique, in which the imaging process is divided into three steps which are carried out in a determined order, the steps and the order being formation of sub-aperture beams at one speed, performing clutter suppression based on estimation of the clutter statistics of the sub-aperture beams, and detection of moving targets, wherein the clutter statistics is estimated from the maximum likelihood estimate of the covariance matrix either for surrounding sub-aperture beams connected to surrounding sub images, or for range bins for the sub-aperture beam, after the sub-aperture beam has been divided into such range bins.
2. A SAR system as claimed in claim 1, wherein the platform moves over a ground surface.
3. A SAR system as claimed in claim 1 or 2, wherein the speed is the ground speed.
4. A SAR system as claimed in any one of claims 1-3, wherein the detection of moving targets comprises combining the sub-aperture beams by relative speed.
5. A SAR system as claimed in any one of claims 1-4, wherein the clutter statistics of the sub-aperture beams are estimated by means of a covariance matrix ~ and the matrix is inverted ~-1 and used, together with a steering vector ~, in the test , where ~ is the measurement vector, H0 is the hypotheses that no target is present, H1 is the hypotheses that a target is present, and .lambda. is the test variable.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US09/703,621 US6518914B1 (en) | 2000-11-02 | 2000-11-02 | Synthetic aperture radar system capable of detecting moving targets |
| US09/703,621 | 2000-11-02 | ||
| PCT/SE2001/002399 WO2002037137A1 (en) | 2000-11-02 | 2001-11-01 | A synthetic aperture radar system capable of detecting moving targets |
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| CA2427606C true CA2427606C (en) | 2011-07-05 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108051812A (en) * | 2018-01-22 | 2018-05-18 | 南京航空航天大学 | Satellite-borne SAR moving target detecting method based on two-dimension speed search |
| CN110646768A (en) * | 2019-10-11 | 2020-01-03 | 深圳大学 | Clutter rank estimation method and device based on uncertain priori knowledge |
Families Citing this family (62)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2428622C (en) * | 2000-11-15 | 2008-01-22 | Harris Corporation | Image formation by passive collection and processing of radio frequency signals illuminating and scattered by cultural features of terrestrial region |
| US6700527B1 (en) * | 2000-11-15 | 2004-03-02 | Harris Corporation | Coherent two-dimensional image formation by passive synthetic aperture collection and processing of multi-frequency radio signals scattered by cultural features of terrestrial region |
| US6633253B2 (en) * | 2001-04-02 | 2003-10-14 | Thomas J. Cataldo | Dual synthetic aperture radar system |
| US7042386B2 (en) * | 2001-12-11 | 2006-05-09 | Essex Corporation | Sub-aperture sidelobe and alias mitigation techniques |
| DE10207465B4 (en) * | 2002-02-22 | 2006-01-05 | Eads Deutschland Gmbh | Method for reducing the false alarm rate in radar images |
| US7109911B1 (en) * | 2002-04-01 | 2006-09-19 | Cataldo Thomas J | Dual synthetic aperture radar system |
| US7573419B2 (en) * | 2003-05-21 | 2009-08-11 | Telefonaktiebolaget Lm Ericsson (Publ) | Method and system for unambiguous angle resolution of a sparse wide-band antenna array |
| US8902100B1 (en) | 2008-03-07 | 2014-12-02 | Rockwell Collins, Inc. | System and method for turbulence detection |
| US8203480B1 (en) | 2003-07-31 | 2012-06-19 | Rockwell Collins, Inc. | Predictive and adaptive weather radar detection system and method |
| US7808422B1 (en) | 2003-07-31 | 2010-10-05 | Rockwell Collins, Inc. | Predictive and adaptive weather radar detection system and method |
| US7852259B2 (en) | 2004-01-23 | 2010-12-14 | Telefonaktiebolaget Lm Ericsson (Publ) | Clutter filtering |
| US6911933B1 (en) * | 2004-05-14 | 2005-06-28 | The United States Of America As Represented By The Secretary Of The Air Force | Dynamic logic algorithm used for detecting slow-moving or concealed targets in synthetic aperture radar (SAR) images |
| US7132975B2 (en) * | 2004-05-28 | 2006-11-07 | Time Domain Corporation | Apparatus and method for detecting moving objects |
| US7333047B2 (en) * | 2004-05-28 | 2008-02-19 | Time Domain Corporation | System and method for spatially diverse radar signal processing |
| CN100365429C (en) * | 2004-11-05 | 2008-01-30 | 清华大学 | Motive target imaging method of synthetic aperture radar |
| US7106243B2 (en) * | 2004-11-23 | 2006-09-12 | Raytheon Company | Technique for enhanced quality high resolution 2D imaging of ground moving targets |
| US7095358B2 (en) * | 2004-11-23 | 2006-08-22 | Raytheon Company | Technique for cancellation of elevated clutter for the detection of fixed and ground moving targets under trees |
| US20060181451A1 (en) * | 2005-02-14 | 2006-08-17 | Honeywell International Inc. | System and method for combining displaced phase center antenna and space-time adaptive processing techniques to enhance clutter suppression in radar on moving platforms |
| US7597950B1 (en) * | 2005-02-28 | 2009-10-06 | Massachusetts Institute Of Technology | Nanoparticles having sub-nanometer features |
| US7154434B1 (en) | 2005-09-12 | 2006-12-26 | The Boeing Company | Anti-personnel airborne radar application |
| US7646326B2 (en) * | 2006-04-28 | 2010-01-12 | The United States Of America As Represented By The Secretary Of The Air Force | Method and apparatus for simultaneous synthetic aperture radar and moving target indication |
| US20090278732A1 (en) * | 2006-04-28 | 2009-11-12 | Paul Antonik | Method and apparatus for simultaneous synthetic aperture radar and moving target indication |
| US7498968B1 (en) * | 2006-05-22 | 2009-03-03 | Sandia Corporation | Synthetic aperture design for increased SAR image rate |
| WO2008021374A2 (en) * | 2006-08-15 | 2008-02-21 | General Dynamics Advanced Information Systems, Inc | Methods for two-dimensional autofocus in high resolution radar systems |
| US7884752B2 (en) * | 2006-12-11 | 2011-02-08 | Telefonaktiebolaget L M Ericsson (Publ) | Radar system and a method relating thereto |
| US8125370B1 (en) | 2007-04-16 | 2012-02-28 | The United States Of America As Represented By The Secretary Of The Navy | Polarimetric synthetic aperture radar signature detector |
| US9244166B1 (en) | 2008-03-07 | 2016-01-26 | Rockwell Collins, Inc. | System and method for ice detection |
| US9864055B1 (en) | 2014-03-12 | 2018-01-09 | Rockwell Collins, Inc. | Weather radar system and method for detecting a high altitude crystal cloud condition |
| US9244157B1 (en) | 2008-03-07 | 2016-01-26 | Rockwell Collins, Inc. | Weather radar threat depiction system and method |
| US9244167B1 (en) | 2008-03-07 | 2016-01-26 | Rockwell Collins, Inc. | Long range weather information display system and method |
| US9057773B1 (en) | 2012-12-06 | 2015-06-16 | Rockwell Collins, Inc. | Weather information display system and method |
| US9846230B1 (en) | 2013-03-15 | 2017-12-19 | Rockwell Collins, Inc. | System and method for ice detection |
| EP2359159B1 (en) * | 2008-11-11 | 2019-05-15 | Saab AB | Sar radar system |
| CN101813765B (en) * | 2010-04-23 | 2012-11-21 | 哈尔滨工业大学 | Noise suppression method based on inhomogeneous space solid array distributed SAR (Specific Absorption Rate) |
| US8237605B2 (en) | 2010-09-21 | 2012-08-07 | Raytheon Company | Target detection from a slow moving radar platform |
| US9223020B1 (en) | 2010-09-28 | 2015-12-29 | Rockwell Collins, Inc. | System and method for weather detection using more than one source of radar data |
| US8907841B2 (en) * | 2011-04-04 | 2014-12-09 | Mitsubishi Electric Research Laboratories, Inc. | Method for detecting targets using space-time adaptive processing |
| DE102011016337B4 (en) * | 2011-04-07 | 2014-11-06 | Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. | Method and device for imaging moving objects superimposed with clutter with radar or sonar |
| CN102221689B (en) * | 2011-06-01 | 2012-09-05 | 中国人民解放军国防科学技术大学 | Multi-channel correcting method for ultra wide-band synthetic aperture radar |
| CN102288962B (en) * | 2011-07-13 | 2013-05-15 | 中国人民解放军国防科学技术大学 | Real-time motion compensation method for ultra-wide band synthetic aperture radar (UWB SAR) |
| US9019146B1 (en) | 2011-09-27 | 2015-04-28 | Rockwell Collins, Inc. | Aviation display depiction of weather threats |
| US9823347B1 (en) | 2014-03-12 | 2017-11-21 | Rockwell Collins, Inc. | Weather radar system and method for high altitude crystal warning interface |
| CN102508244B (en) * | 2011-11-08 | 2013-04-03 | 中国人民解放军国防科学技术大学 | Ground moving target detection and parameter estimation method |
| JP2013195102A (en) * | 2012-03-16 | 2013-09-30 | Mitsubishi Space Software Kk | Apparatus, program, and method for radar image processing |
| US9116244B1 (en) | 2013-02-28 | 2015-08-25 | Rockwell Collins, Inc. | System for and method of weather phenomenon detection using multiple beams |
| CN103616729B (en) * | 2013-11-06 | 2016-05-18 | 中国人民解放军第四军医大学 | A kind of multiple human body target evaluation methods and system based on UWB bioradar |
| US9599707B1 (en) | 2014-01-23 | 2017-03-21 | Rockwell Collins, Inc. | Weather radar system and method with path attenuation shadowing |
| US9535158B1 (en) | 2013-11-21 | 2017-01-03 | Rockwell Collins, Inc. | Weather radar system and method with fusion of multiple weather information sources |
| US9810770B1 (en) | 2014-07-03 | 2017-11-07 | Rockwell Collins, Inc. | Efficient retrieval of aviation data and weather over low bandwidth links |
| US9869766B1 (en) | 2015-01-28 | 2018-01-16 | Rockwell Collins, Inc. | Enhancement of airborne weather radar performance using external weather data |
| CN105068071B (en) * | 2015-07-16 | 2017-10-03 | 中国科学院电子学研究所 | A kind of fast imaging method based on backprojection operator |
| US10809375B1 (en) | 2015-09-14 | 2020-10-20 | Rockwell Collins, Inc. | Radar system and method for detecting hazards associated with particles or bodies |
| US10302815B1 (en) | 2015-10-01 | 2019-05-28 | Rockwell Collins, Inc. | System and method of integrating global convective weather |
| CN105842697B (en) * | 2016-03-25 | 2018-06-01 | 北京理工大学 | Strabismus InSAR joint DEM and GMTI processing methods based on five-element acoustic array |
| CN105842696B (en) * | 2016-03-28 | 2018-04-10 | 北京理工大学 | A kind of strabismus InSAR Ground moving targets detection methods based on rotatable forward sight battle array |
| US10494108B1 (en) | 2016-05-17 | 2019-12-03 | Rockwell Collins, Inc. | System and method for providing icing condition warnings |
| US11378682B2 (en) * | 2017-05-23 | 2022-07-05 | Spacealpha Insights Corp. | Synthetic aperture radar imaging apparatus and methods for moving targets |
| CN108008378B (en) * | 2017-05-26 | 2018-12-14 | 北京航空航天大学 | A kind of SAR false target energy ratio determines method and device |
| CN108020835B (en) * | 2017-11-30 | 2019-12-10 | 中国科学院电子学研究所 | Strong clutter suppression method and device for ground moving target indication GMTI of space-borne Synthetic Aperture Radar (SAR) |
| EP3575830A1 (en) * | 2018-05-28 | 2019-12-04 | Gottfried Wilhelm Leibniz Universität Hannover | Method for assessing an object speed and apparatus and aircraft |
| CN110568434B (en) * | 2019-07-15 | 2022-06-03 | 电子科技大学 | Multi-channel uniform acceleration SAR moving target two-dimensional speed estimation method |
| CN111965642A (en) * | 2020-07-08 | 2020-11-20 | 西安电子科技大学 | Front squint multi-channel SAR-GMTI clutter suppression method based on hypersonic platform |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4965582A (en) | 1984-11-24 | 1990-10-23 | Hellsten Hans O | Method for radar mapping an area and a radar equipment to carry out the method |
| SE456117B (en) | 1984-11-28 | 1988-09-05 | Hans Hellsten | SET FOR RADAR IMAGE OF A AREA, INCLUDING IMAGE OF STRUCTURES HIDDEN BY DIELECTRIC LAYERS AND RADAR PLANT FOR IMPLEMENTATION OF THE SET |
| US5442364A (en) * | 1993-07-22 | 1995-08-15 | The United States Of America As Represented By The Secretary Of The Navy | Alignment and beam spreading for ground radial airborne radar |
| SE517768C2 (en) * | 1995-09-21 | 2002-07-16 | Totalfoersvarets Forskningsins | A SAR radar system |
| US5898399A (en) * | 1996-05-10 | 1999-04-27 | Erim International, Inc. | Subchirp processing method |
| US5805098A (en) * | 1996-11-01 | 1998-09-08 | The United States Of America As Represented By The Secretary Of The Army | Method and system for forming image by backprojection |
| SE507919C2 (en) * | 1997-06-18 | 1998-07-27 | Foersvarets Forskningsanstalt | Ways to produce a three-dimensional image of a land area using a SAR radar |
| SE511952C2 (en) * | 1998-12-18 | 1999-12-20 | Foersvarets Forskningsanstalt | A SAR radar system |
| FR2794869B1 (en) * | 1999-06-09 | 2001-09-07 | Agence Spatiale Europeenne | DEVICE FOR GENERATING AND / OR DETECTING A RADAR SIGNAL |
| US6300914B1 (en) * | 1999-08-12 | 2001-10-09 | Apti, Inc. | Fractal loop antenna |
| DE19938592C2 (en) * | 1999-08-18 | 2003-02-27 | Deutsch Zentr Luft & Raumfahrt | Aircraft or spacecraft-borne radar system with synthetic antenna aperture |
-
2000
- 2000-11-02 US US09/703,621 patent/US6518914B1/en not_active Expired - Lifetime
-
2001
- 2001-11-01 EP EP01981247A patent/EP1337874A1/en not_active Ceased
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- 2001-11-01 WO PCT/SE2001/002399 patent/WO2002037137A1/en not_active Application Discontinuation
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108051812A (en) * | 2018-01-22 | 2018-05-18 | 南京航空航天大学 | Satellite-borne SAR moving target detecting method based on two-dimension speed search |
| CN108051812B (en) * | 2018-01-22 | 2021-06-22 | 南京航空航天大学 | Satellite-borne SAR moving target detection method based on two-dimensional speed search |
| CN110646768A (en) * | 2019-10-11 | 2020-01-03 | 深圳大学 | Clutter rank estimation method and device based on uncertain priori knowledge |
Also Published As
| Publication number | Publication date |
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| CA2427606A1 (en) | 2002-05-10 |
| EP1337874A1 (en) | 2003-08-27 |
| WO2002037137A1 (en) | 2002-05-10 |
| US6518914B1 (en) | 2003-02-11 |
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