CN103616729B - A kind of multiple human body target evaluation methods and system based on UWB bioradar - Google Patents

Abstract

The invention discloses a kind of multiple human body target evaluation methods and system based on UWB bioradar, belong to bioradar human life detection field, the present invention is on to the processing of the echo data collecting, first in each passage, adopt breathing detection algorithm, adaptive cancellation method and Target Recognition Algorithms to process, then carry out relevant treatment according to this result at each interchannel, last setting threshold is removed in passage and is processed residual clutter, and realize target classification simultaneously and number are estimated. The evaluation method of human body target number of the present invention, in order further to realize, the bioradar of multiple human body targets is surveyed and technical foundation has been established in location, contributes to promote bioradar technology and obtain level and the ability of human body information.

Description

A kind of multiple human body target evaluation methods and system based on UWB bioradar

Technical field

The invention belongs to bioradar human life detection field, be specifically related to a kind of multiple human body target evaluation methods and system based on UWB bioradar.

Background technology

Bioradar is a kind of special Radar Technology for life entity target acquisition and identification. This technology is mainly taking human body as the detection of a target, obtains the information of human body target taking the electromagnetic wave of radar emission as carrier. Its maximum advantage is to possess the ability that penetrates the barrier such as wall, ruins, is therefore with a wide range of applications in the field such as national security, emergency management and rescue.

In actual applications, people first pay close attention to whether someone exists, whether have at least people to exist. Therefore bioradar technology is substantially taking the detection of single target as main present stage. Along with the realization of this technology, people can further pay close attention to the quantity of human body target, have on earth how many people to exist. Press down such as search after the earthquake ruins the survivor who buries, counterterrorism operations mid-board monitors the terrorist in building etc. But up to the present, still do not have method to address this problem, particularly without any priori in the situation that.

Summary of the invention

The object of the present invention is to provide a kind of multiple human body target evaluation methods and system based on UWB bioradar, the method, based on many antennas UWB bioradar system, can accurately estimate human body target number under the condition that does not possess priori.

The present invention is achieved through the following technical solutions:

Based on multiple human body target estimating systems for UWB bioradar, comprise radar host computer, aerial array and computer, described radar host computer comprises impulse generator, emitter, central controller, delayer and several receiving elements; Described aerial array comprises 1 transmitting antenna and 3 reception antennas, and transmitting antenna is connected with the emitter of radar host computer, and each reception antenna and a receiving element are connected to form a radar return data channel; The analog-digital converter that described receiving element comprises receiver and is connected with receiver, the output of each analog-digital converter is all connected with central controller, and central controller is realized and being communicated by letter with computer interactive;

Impulse generator produces periodic short pulse signal: a part is delivered to emitter shaping, then radiate by transmitting antenna; Another part narrow pulse signal is sent to delayer and produces control signal, and triggers receiving element echo-signal is selectively received in distance.

Described aerial array adopts linear array arrangement mode, centered by transmitting antenna, the adjacent setting of the first reception antenna and transmitting antenna, the second reception antenna and the 3rd reception antenna are symmetricly set in respectively the both sides of transmitting antenna, and the distance of the second reception antenna, the 3rd reception antenna and transmitting antenna is 0.3～1m.

Described each independently echo data interchannel employing reinforcement isolated from power design.

UWB bioradar adopts impulse system, and exomonental width is controlled at ns rank, and corresponding spectrum width and centre frequency are 500MHz; Transmitting antenna and reception antenna all adopt butterfly dipole antenna, and and radar host computer between use shielding coaxial cable be connected.

Based on multiple human body target evaluation methods for UWB bioradar, comprise the following steps:

1) data acquisition

After several radar return data channel samplings of UWB bioradar system, the echo data obtaining is delivered to computer and carry out Storage and Processing;

2) in passage, process

First, adopt breathing detection algorithm to obtain human body respiration signal to the echo data obtaining; Secondly, adopt adaptive cancellation method to suppress the phase mutual interference of breath signal between different human body target to the human body respiration signal detecting; Finally, setting energy threshold by Target Recognition Algorithms identifies target individual;

3) interchannel processing

To step 2) waveform corresponding to human body target identification point in each passage of recognizing calculate interchannel correlation coefficient r according to formula (1)_ij：

$r_{\mathrm{ij}}=\frac{{\mathrm{\ΣS}}_i{S}_j}{{\left[\mathrm{\Σ}{S}_i^2\mathrm{\Σ}{S}_j^2\right]}^{1/2}}---\left(1\right)$

Wherein, S_iAnd S_jRepresent the waveform on two passages, wherein i, j=1,2,3 ..., and i ≠ j;

Setting threshold A, by the correlation coefficient r calculating_ijContrast with this threshold value A, carry out the differentiation of different target: for the impact point in each channel recognition result, must exist another passage impact point and its coefficient correlation to be greater than the threshold value A of this setting, otherwise be considered as clutter; The impact point that interchannel coefficient correlation is greater than the threshold value A of this setting is regarded as from same target;

4) last, the clutter in each passage is removed, by target classification, obtain human body target number.

Step 2) described breathing detection algorithm is specially:

First, the range information providing according to UWB bioradar system, in the enterprising line slip average treatment of distance, improves the signal to noise ratio of echo data to echo data;

Secondly, remove time-independent static background clutter in echo data;

Again, utilize the narrow-band characteristic of human body respiration, adopt adaptive algorithm that human body respiration is separated with noise;

Finally, carry out LPF according to the gradual feature of human body respiration, obtain the human body respiration signal that detections of radar arrives.

Step 2) described adaptive cancellation method is using the waveform of a certain range points in the echo data after breathing detection algorithm process as input signal, the breath signal of human body target is as with reference to signal before this range points, obtains error signal and go to revise the coefficient of sef-adapting filter with two paths of signals after subtracting each other; If input corresponding a certain target range point signal, this flow process can offset the hangover of previous targets and disturb, and exports the breath signal of this target; If input signal is the hangover that previous targets respiratory movement causes, after offseting, output signal is zero; Wherein, described sef-adapting filter adopts LMS algorithm to realize.

Step 2) described Target Recognition Algorithms is that the data of processing through the method for adaptive cancellation are accumulated in time, obtain the energy-range distribution of one dimension, in this distribution, in human body target respective distances, there will be energy peak, this energy peak setting threshold is had to aimless binary judgement, can identify target.

First, set energy threshold Th1 and dependent thresholds Th2;

Energy threshold Th1 has driftlessness for judgement, chooses impact point energy E_obj, clutter point energy E_clu, work as E_obj/E_cluWhile being greater than energy threshold Th1, judging in this range points for target and be output as 1, otherwise output 0;

Dependent thresholds Th2 is used for choosing clutter point, and the point that energy maximum and waveform and impact point waveform correlation coefficient are less than dependent thresholds Th2 except impact point in recognition window is regarded as clutter point, and this energy is as E_clu。

Described energy threshold Th1 and dependent thresholds Th2 are empirical value, and Th1=2, Th2=0.6.

Compared with prior art, the present invention has following useful technique effect:

Radar antenna array of the present invention is made up of 1 transmitting antenna and 3 reception antennas, and the receiving element that each reception antenna is corresponding with it has formed 3 independently radar return data channel. For same target, the breath signal that different passages detect has high correlation; And for breath signal and the clutter of different target, each interchannel degree of correlation is lower. Therefore the present invention is on to the processing of the echo data collecting, first in each passage, adopt breathing detection algorithm, adaptive cancellation method and Target Recognition Algorithms to process, then carry out relevant treatment according to this result at each interchannel, last setting threshold is removed in passage and is processed residual clutter, and realize target classification simultaneously and number are estimated. The evaluation method of human body target number of the present invention, in order further to realize, the bioradar of multiple human body targets is surveyed and technical foundation has been established in location, contributes to promote bioradar technology and obtain level and the ability of human body information.

Further, UWB bioradar of the present invention adopts impulse system, and exomonental width is controlled at ns rank, and corresponding spectrum width and centre frequency are 500MHz, can ensure penetration capacity and the detectability to human body respiration simultaneously.

Brief description of the drawings

Many antennas of Fig. 1 UWB bioradar system block diagram;

Echo Processing flow chart in Fig. 2 passage;

UWB bioradar echo data after Fig. 3 breathing detection algorithm process;

Fig. 4 interference suppression algorithm schematic diagram;

Fig. 5 passage internal object recognizer schematic diagram

Fig. 6 passage internal object recognition result

The human body target that the different passages of Fig. 7 detect is breathed and clutter;

Two human body targets that the different passages of Fig. 8 detect are breathed;

The clutter that the different passages of Fig. 9 detect;

Figure 10 interchannel handling process;

Figure 11 efficiency evaluation experiment schematic diagram;

When Figure 12 driftlessness, many antennas UWB bioradar is surveyed and target number estimated result;

When Figure 13 single goal, many antennas UWB bioradar is surveyed and target number estimated result;

When Figure 14 Bi-objective, many antennas UWB bioradar is surveyed and target number estimated result;

When Figure 15 tri-target, many antennas UWB bioradar is surveyed and target number estimated result.

Detailed description of the invention

Below in conjunction with concrete drawings and Examples, the present invention is described in further detail, and the explanation of the invention is not limited.

Referring to Fig. 1, the multiple human body target estimating systems that the present invention is based on UWB bioradar are mainly made up of three functional modules: aerial array, radar host computer and computer. Impulse generator in radar host computer produces periodic narrow pulse signal, and a part is delivered to emitter shaping, then radiate by transmitting antenna; A part is delivered to delayer generation control signal triggering receiver echo-signal is selectively received in distance. Delayer adopts the design of digital multi-channel stepping technique, and full accuracy can reach 10ps. Aerial array is made up of four unit: 1 transmitting antenna and 3 reception antennas, all adopt between butterfly dipole antenna and radar host computer and use shielding coaxial cable to connect. Each reception antenna and a receiving element are connected to form a radar return data channel; The analog-digital converter that described receiving element comprises receiver and is connected with receiver. Each interchannel adopts strengthens isolated from power design, can effectively alleviate interchannel echo-signal coupling. Data after each channel sample are delivered to computer and are carried out Storage and Processing. Central controller is mainly used in communicating by letter of computer and radar host computer, realizes the function of parameter setting and transfer of data, uses USB to connect between it and computer.

Because the present invention only relates to the estimation of human body target number, aerial array adopts linear array form, and concrete arrangement mode is: centered by transmitting antenna; Reception antenna 1 is positioned at one side and near its placement; Reception antenna 2 and 3 lays respectively at transmitting antenna both sides and is symmetrically distributed; With its centre-to-centre spacing be 0.3～1m, this lower limit determines by antenna size, the upper limit is relevant with antenna beamwidth. Radar transmitted pulse repetition rate is 128KHz, and triple channel adopts synchronous data collection, and corresponding parameter is as shown in table 1.

Table 1UWB bioradar key job parameter

Time window	80ns
		Original position	5ns
Sampling number	8192
		Sweep speed	16Hz

Below radar return data processing in the multiple human body target evaluation methods based on UWB bioradar of the present invention is elaborated:

One, in passage, process

As shown in Figure 2, be the basic procedure of processing in UWB bioradar passage, each passage echo data all adopts this flow process to process. In passage, process and formed by three key steps: breathing detection algorithm, interference suppression algorithm and Target Recognition Algorithms. Breathing detection algorithm is mainly realized the detection of human body respiration signal; Adopt on this basis adaptive cancellation to suppress the phase mutual interference of breath signal between human body target; Increase because human body target breathing causes energy in its respective distances, finally set energy threshold target is identified.

1. breathing detection algorithm

Comprise following functional module: signal to noise ratio improvement, background removal, self adaptation strengthen and LPF. Wherein, it is the range information that utilizes UWB bioradar to provide that signal to noise ratio is improved, and averages the signal to noise ratio that improves echo data in distance; Background removal is used for removing the time-independent static background clutter of radar return data, subtracts average realization on the employing time; Self adaptation strengthens utilizes the narrow-band characteristic of human body respiration, it is separated with broadband noise, thereby reach the object of enhancing; LPF adopts digital filter, leaches the human body low-pass signal of low frequency.

Referring to Fig. 3, be the UWB bioradar echo data after breathing detection algorithm process, wherein comprise the time and apart from two-dimensional signal, distance represents with pulse two way travel time ns. In these data, human body target, apart near 28ns, presents the periodic undulations of going up in time. Extract the wherein waveform of energy ultimate range point, can obtain the human body respiration signal of detections of radar. As can be seen from the figure,, owing to being subject to the modulation of human body respiration motion, UWB bioradar echo data presents obvious hangover. In the time that radar is used for multiple target acquisition, the hangover meeting of previous targets forms and disturbs subsequent target, affects result of detection when serious. Therefore, it being suppressed is to realize the key that multiple human body target numbers are estimated.

2. interference suppression algorithm

Disturb and suppress handling process as shown in Figure 4, wherein input signal is the waveform of a certain range points in the UWB bioradar echo data after breathing detection algorithm process, reference signal is this range points breath signal of human body target before, obtains error signal and remove to revise adaptive filter coefficient after two paths of signals subtracts each other. If input corresponding a certain target range point signal, this flow process can offset the hangover of previous targets, exports the breath signal of this target; If input signal is the hangover that previous targets respiratory movement causes, after offseting, output signal is zero. Sef-adapting filter adopts LMS algorithm to realize.

3. Target Recognition Algorithms

After above algorithm process, in UWB bioradar echo data in range points corresponding to target, because the effect of human body respiration can present stronger energy. These data are accumulated in time to the energy-range distribution that obtains one dimension, in this distribution, in human body target respective distances, there will be energy peak, its setting threshold is had to aimless binary judgement, can identify target.

Target Recognition Algorithms is illustrated as shown in Figure 5, threshold value Th1 and Th2 is set, N in figure_winRepresent recognition window, it is relevant with the range resolution ratio of system, adopts 2 times of distances corresponding to UWB radar pulse width (N that counts_win=8ns）；E_objRepresent impact point energy; E_cluRepresent clutter point energy.

Energy threshold Th1 has driftlessness for judgement, works as E_obj/E_cluWhile being greater than energy threshold Th1, illustrating that impact point energy is significantly greater than clutter point energy, is the possibility very large (judge accordingly in this range points and have human body target in other words) of target, judge in this range points for target and be output as 1, otherwise output 0.

Dependent thresholds Th2 is used for choosing clutter point, and following rule is observed in choosing of clutter point: in recognition window, except impact point, energy maximum and waveform and impact point waveform correlation coefficient are less than the point of threshold value Th2.

Wherein, the energy threshold Th1 of institute and dependent thresholds Th2 are empirical value, and Th1=2 represents to be significantly higher than clutter point because human body respiration causes impact point energy; Th2=0.6, it is low that coefficient correlation is less than these value representation two waveform degrees of correlation, and the probability that clutter point is correctly chosen is large. Concrete treatment step is:

First, ask the coefficient correlation of clutter point waveform and the impact point waveform of selection, then by this coefficient correlation and Th2 comparison, this coefficient correlation is greater than Th2=0.6, illustrates that both degrees of correlation are high, and the clutter point of selection and impact point similarity degree are higher, illustrate that now definite clutter point energy is incorrect, only have this coefficient correlation to be less than Th2=0.6, just illustrate that selected clutter point is exactly clutter point, impact point is exactly impact point.

Through Fig. 5 Target Recognition Algorithms Output rusults after treatment as shown in Figure 6, this figure is that certain surveys the data that in the experiment of two human body targets, UWB bioradar system second channel gathers. Identified according to two human body targets at 14ns and 23ns place in the known figure of the priori of target range, but there is the residual clutter producing due to erroneous judgement in 68ns and 84ns place. For correct estimating target number, by the interchannel processing of proceeding based on many antennas UWB bioradar.

Two, interchannel processing

Referring to Fig. 7, show the many antennas UWB bioradar system that adopts the present invention to use, survey after a certain human body target the breath signal of this human body target that 3 radar return data channel detect. As can be seen from the figure, 3 road respiratory waveforms are consistent, present very high degree of correlation. This is that because three reception antennas independently receive and sample, the breath signal therefore detecting in different pieces of information passage in theory should be in full accord because of the echo-signal producing for same target. In figure, dotted line represents the clutter waveform in a certain passage range points, and it and respiratory waveform differ greatly, and degree of correlation is lower.

Fig. 8 has shown the breath signal detecting after two human body targets of many antennas UWB bioradar system detection that adopt the present invention to use, and both shape differences are larger. This is that the respiratory waveform degree of correlation therefore detecting is lower because different target respiratory rhythm always there are differences.

Fig. 9 has shown two two-way noise signals that radar return data channel detects. There is certain randomness because clutter produces, add and derive from different pieces of information passage, the inevitable uniformity that do not exist.

More than analyze and show, for many antennas UWB bioradar:

(1) breathing of the same target that different passages detect is height correlation;

(2) the breathing degree of correlation of the different target that different passages detect is lower;

(3) clutter and human body target breathing degree of correlation are low;

(4) degree of correlation between clutter is low.

Therefore consider to carry out relevant treatment at interchannel, can not only effectively remove clutter, thereby and can distinguish the estimation of human body target realize target number.

Figure 10 has shown the basic procedure of interchannel processing, first calculates interchannel coefficient correlation according to the result of 3 passage human body target identifications, calculates in pairs coefficient correlation by the waveform that in each channel recognition result, impact point is corresponding at interchannel, and method is as follows:

$r_{\mathrm{ij}}=\frac{{\mathrm{\ΣS}}_i{S}_j}{{\left[\mathrm{\Σ}{S}_i^2\mathrm{\Σ}{S}_j^2\right]}^{1/2}}---\left(1\right)$

Si and Sj represent two waveforms on passage, wherein i, j=1,2,3 ..., and i ≠ j.

Setting threshold A, by the correlation coefficient r calculating_ijContrast with this threshold value A, carry out the differentiation of different target, rule is as follows: (1), for the impact point in each channel recognition result, must exist another passage impact point and its coefficient correlation to be greater than this threshold value A, otherwise be considered as clutter; (2) impact point that interchannel coefficient correlation is greater than this threshold value A is regarded as from same target.

Correlation coefficient r_ijMore approach 1 expression two waveform degrees of correlation higher, uniformity is better. After above rule process, the residual clutter in each passage is removed, and target is classified simultaneously, thereby obtains target number. Threshold value A is an empirical value herein, and great many of experiments shows that this value is set as 0.6 o'clock performance the best.

By concrete contrived experiment, the usefulness of the inventive method is evaluated below:

As shown in figure 11, this UWB bioradar penetrates brick wall that a stifled 28cm is thick and surveys after to wall. Detection process comprises 4 kinds of situations: there is no target, 1 target (P1), 2 targets (P1, P2), 3 targets (P1, P2, P3). Wherein P1 is just to transmitting antenna, is positioned at about 3m place after wall; 20 ° of the relative transmitting antenna left avertences of P2, are positioned at about 4m after wall; 20 ° of the relative transmitting antenna right avertence of P3, are positioned at about 5m after wall. While having target, each target face is stood to wall and is kept static.

Figure 12～15 have shown above-mentioned four kinds of results that situation is corresponding, and in figure, each row is distinguished respective channel 1,2 and 3 under upper; It is interior through interference suppression algorithm data after treatment that each row are respectively passage from left to right, one dimension energy-range distribution that these data are corresponding, and human body target recognition result. In addition, after interchannel relevant treatment, the fork-shaped mark of the clutter point in each passage, the triangle mark of different directions for the target distinguishing. As can be seen from these figures, the target number identifying in 4 kinds of situations is with actual in full accord. Therefore, without any priori in the situation that, the identification that the present invention is the multiple human body targets of bioradar and number are estimated to provide a kind of effective method, contribute to promote bioradar technology and obtain level and the ability of human body information.

Should be understood that, for those of ordinary skills, can be improved according to the above description or convert, and all these improvement and conversion all should belong to the protection domain of claims of the present invention.

Claims (5)

1. the multiple human body target estimating systems based on UWB bioradar, is characterized in that, bagDraw together radar host computer, aerial array and computer, described radar host computer comprise impulse generator, emitter,Central controller, delayer and several receiving elements; Described aerial array comprises 1 transmitting antennaWith 3 reception antennas, transmitting antenna is connected with the emitter of radar host computer, each reception antenna and oneReceiving element is connected to form a radar return data channel; Described receiving element comprise receiver and withThe analog-digital converter that receiver is connected, the output of each analog-digital converter is all connected with central controller,Central controller is realized and being communicated by letter with computer interactive;

Impulse generator produces periodic short pulse signal: a part is delivered to emitter shaping, then passes throughTransmitting antenna radiate; Another part narrow pulse signal is sent to delayer and produces control signal, and touchesTransmission/reception unit selectively receives in distance echo-signal;

Described aerial array adopts linear array arrangement mode, centered by transmitting antenna, the first reception antenna withThe adjacent setting of transmitting antenna, the second reception antenna and the 3rd reception antenna are symmetricly set in respectively transmitting antennaBoth sides, and the distance of the second reception antenna, the 3rd reception antenna and transmitting antenna is 0.3～1m.

2. a kind of UWB bioradar that can estimate multiple human body targets according to claim 1System, is characterized in that, described each independently echo data interchannel employing reinforcement isolated from power design.

3. can estimate multiple human body targets according to a kind of described in any one in claim 1～2UWB bioradar system, is characterized in that, UWB bioradar adopts impulse system, transmittingThe width of pulse is controlled at ns rank, and corresponding spectrum width and centre frequency are 500MHz; TransmittingAntenna and reception antenna all adopt butterfly dipole antenna, and and radar host computer between use shielding coaxial lineCable connects.

4. the multiple human body target evaluation methods based on UWB bioradar, is characterized in that, bagDraw together following steps:

1) data acquisition

After several radar return data channel samplings of UWB bioradar system, by the echo obtainingData are delivered to computer and are carried out Storage and Processing;

2) in passage, process

First, adopt breathing detection algorithm to obtain human body respiration signal to the echo data obtaining; Secondly,Adopt adaptive cancellation method to suppress to breathe and believe between different human body target to the human body respiration signal detectingNumber phase mutual interference; Finally, setting energy threshold by Target Recognition Algorithms identifies target individual;

Described breathing detection algorithm is specially:

First, the range information providing according to UWB bioradar system, to echo data in distanceCarry out moving average processing, improve the signal to noise ratio of echo data;

Secondly, remove time-independent static background clutter in echo data;

Again, utilize the narrow-band characteristic of human body respiration, adopt adaptive algorithm that human body respiration and noise are enteredRow separates;

Finally, carry out LPF according to the gradual feature of human body respiration, obtain the human body that detections of radar arrivesBreath signal;

Described adaptive cancellation method is by a certain distance in the echo data after breathing detection algorithm processFrom the waveform of point as input signal, before this range points the breath signal of human body target as with reference to signal,After subtracting each other with two paths of signals, obtain error signal and go to revise the coefficient of sef-adapting filter; If input is correspondingA certain target range point signal, this flow process can offset the hangover of previous targets and disturb, and exports exhaling of this targetInhale signal; If input signal is the hangover that previous targets respiratory movement causes, output letter after offsetingNumber be zero; Wherein, described sef-adapting filter adopts LMS algorithm to realize;

Described Target Recognition Algorithms is that the data of processing through the method for adaptive cancellation are entered in timeRow is accumulated, and obtains the energy-range distribution of one dimension, in this distribution, in human body target respective distances, there will be energyAmount peak value, has aimless binary judgement to this energy peak setting threshold, can identify target;

The described aimless binary judgement that has refers to:

First, set energy threshold Th1 and dependent thresholds Th2; Energy threshold Th1 has or not for judgementTarget, chooses impact point energy E_obj, clutter point energy E_clu, work as E_obj/E_cluBe greater than energy threshold Th1Time, judge in this range points for target and be output as 1, otherwise output 0; Dependent thresholds Th2 is used forChoose clutter point, in recognition window except impact point energy maximum and waveform and impact point waveform correlation coefficient littleBe regarded as clutter point in the point of dependent thresholds Th2, this energy is as E_clu；

3) interchannel processing

To step 2) waveform corresponding to human body target identification point in each passage of recognizing be according to formula (1)Calculate interchannel correlation coefficient r_ij：

$r_{ij}=\frac{{\mathrm{\ΣS}}_i{S}_j}{{\[{\mathrm{\ΣS}}_i^2{\mathrm{\ΣS}}_j^2\]}^{1/2}}---\left(1\right)$

Wherein, S_iAnd S_jRepresent the waveform on two passages, wherein i, j=1,2,3 ..., and i ≠ j;

Setting threshold A, by the correlation coefficient r calculating_ijContrast with this threshold value A, carry out differenceThe differentiation of target: for the impact point in each channel recognition result, must have another passage impact pointBe greater than the threshold value A of this setting with its coefficient correlation, otherwise be considered as clutter; Interchannel coefficient correlation is greater than thisThe impact point of the threshold value A of setting is regarded as from same target;

4) last, the clutter in each passage is removed, by target classification, obtain human body target number.

5. a kind of multiple human body target estimations based on UWB bioradar according to claim 4Method, is characterized in that: described energy threshold Th1 and dependent thresholds Th2 are empirical value, andTh1＝2，Th2＝0.6。