A Multi-Radar Multi-Target Based On Particle Filter For TBD Algorithm

The technology of track-before-detect does not strictly divide the detection and tracking boundaries.It is an effective method to detect and track weak targets by accumulating multi-frame energy to improve the signal-to-noise ratio.On this basis,The technology of track-before-detect based on particle filter can theoretically solve the problem of target tracking in non-linear and non-Gaussian situations,and the accuracy is close to the optimal estimation.In recent years,PF-TBD has gradually become a hot spot in the field of TBD technology,which has attracted wide attention of scholars at home and abroad,and has achieved a series of results.In recent years,with the gradual development of multi-radar cooperative detection technology,early warning systems mostly use radar networking system for joint detection of unknown number of targets.However,the traditional PF-TBD mostly uses the measurement information of a single sensor.Furthermore,in multi-target detection and tracking,the number of targets is usually fixed or the maximum number of known targets is required.Thus it can not be directly applied to the problem of multi-radar target detection and tracking.At the same time,multi-radar multi-target cooperative detection and tracking still has the problems of multi-radar with different system errors,multi-radar information fusion,accurate estimation of target number and mutual interference when target position is close to each other.Aiming at the problem of multi-radar multi-target detection,this paper studies the pre-detection tracking algorithm of multi-radar multi-target based on particle filter when the number of targets is unknown.The main research contents are as follows:1.The basic principle and system model of particle filter pre-detection tracking algorithm are introduced.At the same time,the common algorithms of multi-radar space-time registration and particle weight fusion are introduced,and the concrete implementation steps of multi-radar single-target PF-TBD algorithm are described.2.In view of the unknown number of targets detected by multi-radar joint detection,a multi-radar multi-target PF-TBD algorithm(MEPF-TBD)based on measurement cancellation is proposed.The algorithm establishes a multi-radar,multi-target and double-layer particle filter structure,and detects and tracks multiple targets by tracking module particles and detection module particles respectively.The target detection module is responsible for detecting new targets,and the target tracking module is responsible for tracking the detected targets.In the target detection module,the idea of measurement elimination is introduced.The total measurement is subtracted from the detected target measurement,and the radar measurement is modified.Finally,the target is detected and the state of the target is estimated based on the modified measurement.Compared with the traditional PF-TBD algorithm,the algorithm achieves multi-target detection and tracking in the case of unknown number of targets,especially in the case of close target location,the detection effect is stable.3.Aiming at the shortcomings of multi-radar multi-target PF-TBD algorithm based on measurement elimination,such as high complexity,time-consuming and special radar measurement requirements,a multi-radar multi-target PF-TBD algorithm based on particle weight correction(WCPF-TBD)is proposed.Based on the structure of multi-radar multi-target double-layer particle filter,the method of particle weight correction and particle clustering is used to detect multi-target.The particle distribution in tracking particle swarm is modified by twice resampling to detect and eliminate false targets in time.Compared with the multi-radar multi-target PF-TBD algorithm based on measurement cancellation,this algorithm not only achieves similar detection results,but also has lower complexity and less time-consuming.