Research On Radar Target Detection Based On PF-TBD Algorithm

With the increasing development of radar technology,the types of detectable targets are also more abundant,and the applicable scenarios are also more diverse.In complex scenarios,high-intensity clutter and noise will seriously affect the detection and tracking of the target by the radar,especially the problem of detection threshold setting and data correlation calculation will become very troublesome.Therefore,how to improve the radar system's performance in detecting and tracking weak targets is a very important issue today.By improving the radar signal processing algorithm,it can effectively improve its performance in the detection and tracking of weak targets.Under the conditions of strong clutter,strong interference and low signal-to-noise ratio,the detection of weak targets is often difficult.Tracking before detection(TBD)algorithm can effectively improve the performance of detecting weak targets under such harsh conditions.Its implementation is to use the joint processing of multi-frame data to achieve the accumulation of signal energy.Besides,the algorithm combines the process of target detection and tracking to achieve a simultaneous output of results.Particle filter(PF)is a recursive Bayesian filter algorithm.Its main feature is that it can be used in nonlinear systems to approximate the target state by collecting a large number of sample particles in the state region.This article focuses on the basic principles and different application scenarios of the TBD algorithm based on particle filtering.The main work is as follows:1.The basic principles of DBT and TBD radar signal processing are summarized,and their applicable scenarios and advantages and disadvantages are compared.The sequential Bayesian filtering framework is summarized,and the particle filtering algorithm,which is one of its approximated algorithms,is introduced.2.The basic principle of the pre-detection tracking(PF-TBD)algorithm based on particle filtering is introduced.The pre-detection tracking problem in Rayleigh distribution and K distribution clutter is studied.Through simulation experiments,the effectiveness of the PF-TBD algorithm based on amplitude information is verified.3.The radar application scenarios of the PF-TBD algorithm are studied.Taking the target detection and tracking problem of continuous wave radar as the application background,the system and measurement model of the PF-TBD algorithm were constructed;and the phase likelihood function was introduced to optimize the calculation increase caused by the Bessel function;through simulation scenarios And the actual situation of the ground-based radar detecting the vehicle's motion path,combined with the measured data,from the two aspects of detection performance and tracking performance,the algorithm processing effect is analyzed,and the traditional detection and tracking method is compared with PF-TBD.4.For the radar of the airborne moving platform,the concept of space-time model is given,and the clutter model is constructed based on the characteristics of the airborne radar,and the clutter covariance matrix is estimated based on the environmental information;A STAP-TBD algorithm processing framework suitable for airborne platforms was established,and the performance of the algorithm was analyzed using simulation experiments.