Study On Integrated Detection And Tracking Algorithms Assisted By Multi-Information For Bistatic Radar

In recent years,with the rapid development of science and technology and guided weapons,the radar combat environment has become increasingly complex,and the requirements for target tracking technology have become higher and higher.When there are a lot of clutter and interference in the detection environment,traditional tracking algorithms may have a large number of false alarms and missed detections,making it difficult to detect weak targets and form continuous tracks.Therefore,the theory of fully mining prior information to assist tracking algorithms has become a research hotspot in the field of target tracking.Based on the traditional tracking algorithm,the existing target position-based detection and tracking integration algorithm utilizes the prior target position distribution output by the radar in the tracking stage to realize the coupling of the detection and tracking process,which improves the detection and tracking performance of the system.At present,a lot of work has been achieved in the research on the detection and tracking integration algorithm,but there are still some technical problems that need to be further studied:（1）In sufficient use of prior information.Existing algorithms only use target location information in the data association process.When there is a lot of interference and clutter in the environment,there will be many false alarms in the gate,resulting in a low probability of correct association.（2）Receive working parameters and design relatively solidified.Under the traditional radar signal processing framework,the false alarm probability is set for the storage and calculation capabilities of the signal processor.In order to avoid overload,the value is usually low,and the typical value is 10^-6.The target echo amplitude may be smaller than the detection threshold,resulting in target loss.With the improvement of the capability of the signal processor,it is allowed to appropriately lower the detection threshold to improve the target detection ability.However,a lower threshold will bring too many false alarms,so that the track cannot be terminated in time when the target suddenly disappears.（3）Simplify complex background models.Most of the current research assumes that the background clutter obeys the Rayleigh distribution,but the clutter form in the actual scene is more complex（for example,the statistical characteristics of sea clutter are more suitable to be described by the K distribution model）.Using existing algorithms can cause model mismatch,resulting in reduced algorithm performance.In view of the above problems,this thesis carries out the following work based on the background of bistatic radar detection:1.Reasonable use of target prior information to assist the tracking process can improve the performance of the system.However,the existing tracking algorithms have a single auxiliary information,and there is a problem that the probability of correct data association is low in the background of strong clutter.To this,this thesis introduces amplitude information in the data association process,and studies an integrated detection and tracking algorithm assisted by multiple information such as target position and echo amplitude.This thesis deduces the association probability of the Probabilistic Data Association（PDA）algorithm with the aid of multiple information,which improves the accuracy of data association and target tracking accuracy.2.The traditional method uses relatively fixed receiving working parameters,which is prone to the loss of weak targets.For weak target detection requirements in complex backgrounds,the target detection capability can be improved by lowering the threshold reasonably.In this thesis,the track termination criterion is introduced to relax the threshold setting rules,and the average false alarm probability and detection probability of the gate are calculated,in order to reduce the detection threshold and improve the target detection performance under the premise that the correct track termination probability is constant.3.The existing detection and tracking integration algorithm simplifies the complex background model,and can realize the complete detection and tracking joint processing under the Rayleigh distribution clutter.However,there is a problem of modeling mismatch in the background of sea clutter.In this thesis,combined with the multiple prior information such as target position and echo amplitude obtained by the radar in the target tracking stage,the Bayesian detection threshold designed by the wave gate constant false alarm criterion and the track termination criterion and the PDA association assisted by multiple information are deduced in detail.The application background of the integrated detection and tracking algorithm assisted by multi-information is expanded.To sum up,under the background of strong clutter dual-base detection,in view of the low probability of correct data association in the current tracking algorithm,the introduction of multi-information auxiliary data association improves the probability of correct track association;for the weak target detection problem,the track termination criterion improves the detection probability of weak targets on the premise of ensuring a constant track termination probability;for the target detection problem in the background of sea clutter,an integrated detection and tracking algorithm assisted by multi-information based on the K distribution model is studied.The algorithm significantly improves the performance for sea targets.Finally,the thesis simulates the detection and tracking integration algorithm aided by multiple information in case of Rayleigh distribution and K distribution clutter respectively.The simulation results show that the introduction of multivariate information aid and track termination criterion can greatly improve the performance of radar target tracking,and can achieve the target tracking performance in complex environments.Effective tracking of weak targets in the background.