US 20120082006 A1 Résumé Disclosed are systems and methods that can be used to detect shooters. The systems and methods described herein use arrival times of a shockwave, produced by a shot, at a plurality of sensors to assign weights to each of the plurality of sensors, and determine a shot trajectory based on the assigned weights.
Revendications(10) 1. A method for operating a multi-sensor shooter detection system, comprising
providing a plurality of sensors, determining arrival times of a shockwave produced by a shot at each of the plurality of sensors, determining a time residual based at least in part on the arrival times, determining a contribution of each the arrival times to the time residual, assigning a weight to each of the plurality of sensors based on the contribution, and determining a shot trajectory based on the weight. 2. The method of 3. The method of 4. The method of 5. The method of 6. The method of 7. The method of 8. The method of 9. The method of 10. The method of Description This application is a continuation application of U.S. patent application Ser. No. 11/710,044, filed Feb. 23, 2007, which is a divisional application of U.S. patent application Ser. No. 10/925,876, filed Aug. 24, 2004, the entire contents of which are incorporated herein by reference. The present invention relates to law enforcement technologies and security, and more particularly to methods and systems for estimating the location of a shooter firing a supersonic projectile based on shockwave-only information. Systems and methods are known that can determine the general direction and trajectory of supersonic projectiles, such as bullets and artillery shells, by measuring parameters associated with the shockwave generated by a projectile. One such system, described in U.S. Pat. No. 5,930,202 utilizes a distributed array of acoustic sensors to detect the arrival times, amplitudes and frequency characteristics of a projectile's shockwave and the muzzle blast from a firearm. The time of arrival (TOA) information for the shockwave can be used to determine the projectile's trajectory: azimuth, elevation, and intercept with an arbitrary plane in the system coordinate frame. With additional information from the muzzle blast, an accurate location of the origin of the projectile and a line of bearing to the origin of the projectile can be determined. When the muzzle blast is masked, shadowed, silenced or otherwise distorted, at least the bullet trajectory can be estimated from the shockwave alone. Conventional systems typically employ an antenna with a plurality of acoustic sensors, which can be relatively closely spaced (e.g., 1 meter apart) or widely dispersed (e.g., mounted on a vehicle or carried by soldiers on a battlefield), with each sensor measuring shockwave pressure omni-directionally at its respective location. One exemplary antenna may include, for example, a total of 7 omni-directional microphones, with 6 microphones distributed over the surface of a sphere (approx. diameter 1 m) and the seventh microphone located in the center of the sphere. An arrangement with less than 7 sensors can produce objectionable lobes in the spatial sensitivity pattern of the sensor array. Sensor positions can shift over the service life of a deployed system and/or sensor performance can degrade over time for various reasons. Occasionally, some sensors may stop operating altogether. It would therefore be desirable to provide a system and method that compensates for changes in sensor position and sensor performance by calibrating themselves automatically or with operator assistance. The invention is directed to a method for calibrating sensor positions based on shock and muzzle measurements processed from a series of shots fired from a known location and in a known direction, as well as an approach for dynamically adapting shock-only shooter estimation algorithms to compensate for sensor degradation and/or loss. According to one aspect of the invention, a method for calibrating relative sensor positions of sensors in a shooter detection system includes the steps of determining approximate relative location information of the sensors, firing at least two shots having different known shooter positions and known bullet trajectories, determining a time difference between a muzzle-blast arrival time and a shockwave arrival time for each of the sensors and for each shot, and determining the relative sensor positions that produce a minimum residual of the time differences for the at least two shots. Embodiments of the invention may include determining the relative sensor positions by a least-squares search. The least-squares search can be initialized from a previous known location of the sensors or alternatively from an approximately measured location of the sensors. Any one of the sensors can be selected as a reference sensor and the relative muzzle-blast arrival times and shockwave arrival times can be computed for each sensor relative to the reference sensor. According to another aspect of the invention, a method for compensating for sensor degradation in a multi-sensor shooter detection system includes the steps of determining a time of arrival of shockwaves produced at the sensors by incoming shots, performing a least-squares regression for the shockwave arrival times at the sensors to determine a time residual, observing a contribution of each of the sensors to the time residual for a plurality of shots, and assigning a weight for each sensor, said weight being inversely proportional a contribution of said sensor to the time residual. Embodiments of the invention may include normalizing the contribution to an observed maximum time of arrival difference. In addition, a weighted shockwave arrival time can be computed that enhances a contribution from sensors that have a greater reliability. With this approach, the shooter position and bullet trajectory can be determined from a time residual computed with the weighted shockwave arrival time. Any weight that has been changed due to sensor malfunction can be adjusted when the sensor has been repaired. Further features and advantages of the present invention will be apparent from the following description of preferred embodiments and from the claims. The following figures depict certain illustrative embodiments of the invention in which like reference numerals refer to like elements. These depicted embodiments are to be understood as illustrative of the invention and not as limiting in any way. The invention is directed to systems and methods that are able to compensate for changes in the position and performance of acoustic sensors that detect shockwave signals from a supersonic projectile to determine the projectile's trajectory. In particular, the systems and methods described herein can calibrate themselves automatically or with operator assistance in the event that one or more sensors change their relative position, malfunction or fail. Generally, an acoustic system for shooter localization according to the invention utilizes a widely distributed array of acoustic sensors that detect the leading edge of a projectile's shockwave and the muzzle blast from the apparatus used to launch the projectile, for instance a rifle. The wave arrival times of the shockwave and muzzle blast are measured for each waveform type at the sensors. This time of arrival (TOA) information for the shockwave and blast wave can be used to determine the projectile's trajectory, a line of bearing to the origin of the projectile, and the distance from a sensor to the shooter. Although ideally the shock waveform contains useful information about the distance the shockwave has propagated, realistically the shock waveform will often be contaminated by ground reflections and forward scattering and other multi-path propagation, so that it can be difficult to reliably extract distance information solely from shock waveform shape or duration. For trajectory estimation, the system relies primarily upon measuring arrival time of the waveform based on leading edge detection, as the leading edge is not corrupted by multi-path propagation. These same sensors that detect the shockwave can be used to localize the muzzle blast if the muzzle blast signal at the sensors is sufficiently discernable from the shockwave and if the muzzle blast signal can be assumed to travel a direct line-of-sight between the muzzle and the sensors. The ability to localize the muzzle blast is used in conjunction with the shockwave information to very accurately locate the projectile's origin. However, relying solely on muzzle blast may not be a reliable measure for locating the projectile's origin, as it is possible to silence the blast. Furthermore, the muzzle blast can be attenuated by interfering manmade structures (e.g. buildings) or natural structures (e.g. hills). Therefore, in actual deployment of the system, muzzle blast information is used secondarily to the shockwave information. However, a signal from a controlled muzzle blast can be used to calibrate the system. An acoustic counter shooter system according to the invention is generally illustrated in Referring now to Measurements of a shockwave's pressure and arrival time at five or more of the aforedescribed sensors are sufficient to determine uniquely the shooter location, bullet trajectory, and caliber. As depicted in the diagram of The time of arrival is equal to the time
it takes for the projectile to travel the distance |{right arrow over (A)}
wherein t The CPA (or |{right arrow over (R)}
M The velocity V of the projectile can be assumed to be constant along its trajectory, if the sensors are closely spaced, so that there is insignificant loss of speed between the times the projectile radiates to the different sensors. In a more general case, however, a mathematical ballistics model that predicts the arrival time of a shockwave at any general point in space as a function of the full set of parameters can be used. It is derived from physical principles, and has an accuracy of approximately 10 parts per million (ppm). The mathematical model is described in detail in U.S. Pat. No. 6,178,141, the content of which is incorporated herein by reference in its entirety. For comparison, conventional empirically derived ballistic models have nominal 1 m accuracy at 1 km, or 1000 ppm. The ballistic model includes the bullet drag coefficient C
Once the caliber is found, its unique drag coefficient C
The sensor arrangement of The relative positions in space of the sensors may change over time due to mechanical changes, such as bending or other transformations, thereby degrading the accuracy of estimation of the shooter position from TDOA differences. It is therefore important to be able to accurately calibrate the sensor positions in the field, either in scheduled intervals or when otherwise warranted, for example, when erroneous measurements are suspected. As described in U.S. Pat. No. 5,930,202, the exact sniper position along the bullet trajectory can be computed if the muzzle blast wave can be reliably detected in addition to the projectile's shockwave, assuming that the sensor coordinates are accurately known. It should be noted, however, that only the relative positions of the sensors, and not their absolute positions in space, are required. In the present approach, the inverse problem is solved in that the relative coordinates of the sensors in space are determined from a known shooter position and the detected shockwave. The exemplary sensor array In other words, by adding the muzzle-blast equation t The least-squares gradient search method or the genetic algorithm (GA) attempt to minimize the RMS residual fit to all the relative sensors positions (Cx The RMS residual is defined as
It has been found that the sensor positions relative to the reference sensor can be computed quickly and reliably by using an evolutionary genetic algorithm (GA). GAs mimic natural evolutionary principles and apply these to search and optimization procedures. Most classical point-by-point algorithms use a deterministic procedure for approaching the optimum solution, starting from a random guess solution and specifying a search direction based on a pre-specified transition rule, such as direct methods using an objective function and constraint values and gradient-based methods using first and second order derivatives. However, the latter methods have disadvantages, for example, that an optimal solution depends on the selected initial solution and that most algorithms get “stuck” at a sub-optimal solution. Unlike classical search and optimization methods, a GA begins its search with a random set of solutions, instead of just one solution. Once a random population of solutions is created, each is evaluated in the context of the nonlinear programming problem and a fitness (relative merit) is assigned to each solution. In one embodiment, the fitness can be represented by the Euclidean distance between a calculated solution and the measured solution, as defined in Eq. (6) above. Intuitively, an algorithm producing a small value of Δτ When applying the GA to arrive at a solution for the sensor location, the GA uses as a chromosome an initial population of sensor coordinates that can be randomly selected or can have values representing previously measured and/or otherwise determined or estimated sensor locations. Typically, a maximum number of iterations for the GA is performed. For example, in each generation, the “best” individual is allowed to survive unmutated, whereas e.g. the top 100 individuals, as judged by their fitness, also survive, but are used to create the next 100 individuals from pairs of these survivors using crossover/mutation/reproduction operators, as described for example in Kalyanmoy Deb, While least-squares estimation algorithms are robust to Gaussian noise in the measurement of shockwave TOA, any consistent bias in these measurements, for example, due to changes in sensor sensitivity over time, will impact the reliability of the localization estimation. Moreover, a partial or complete loss of a sensor can undermine any assumptions of symmetry that may be inherent in such algorithms. One approach to correct for sensor degradation/loss is to observe the contribution |τ
The time of arrival τ If, as mentioned above, the performance of the array in detecting particular shots is affected by loss of symmetry, then the maximum possible value of Δτ In other words, instead of minimizing the value of the residual of Eq. (7), the value of
is minimized. The effect of weighting the residual function by W While the invention has been disclosed in connection with the preferred embodiments shown and described in detail, various modifications and improvements thereon will become readily apparent to those skilled in the art. Accordingly, the spirit and scope of the present invention is to be limited only by the following claims. Classifications
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