Research On Weak Signal Detection And Tracking Filter Method In Passive Detection

Passive detection system uses FM signals, TV signals and so on as its external illuminators to detect the reflection signals of air targets. After correlation detection processing, parameters of target echo signals such as time delay and Doppler frequency are estimated, so that the goal of tracking and detection is achieved. As a bi-static radar system, passive detection system itself does not radiate electromagnetic signals, and has the advantages of anti-interference, anti-stealth and good survivability, so it has bright future and important application value. One of its main techniques is to extract weak target echo signal submerged by strong noise and clutter. This paper studies on the passive detection system based on FM illuminator, and deeply researches on the detection method of weak target echo and filtering method of multi-target tracking. The main innovations are as follows:Firstly, for the problem of direct path signal which is submerged by multi-path clutter, a new extraction method based on variable step training ST-CMA blind equalization algorithm is proposed. This new algorithm uses a small antenna array to receive reference signal with comprehensive utilization of spatial and temporal degrees of freedom. Compared with the traditional extraction method based on temporal CMA blind equalization algorithm, it is not limited by time delays of multi-path clutter, so it is more effective and robust. Furthmore, the training step is adjusted during iteration and this variable step training makes the convergence rate increase. This method provides reference signal for signal detection processing.Secondly, to improve the detection performance at the circumstance of multi-range gates, a detection method based on core vector regression algorithm is proposed. The range samples are projected onto the feature space, and the radius of the smallest enclosing ball is unchanged in the iterative process. This method has some anti-noise performance. Compared with traditional CA-CFAR method, this new algorithm is more suitable to multi-range gate condition.Thirdly, for the problem of weak echo detection, a new weak signal detection algorithm is presented, which is called multi-stage detection algorithm. This new algorithm uses batch extensive cancellation algorithm to solve the masking effect caused by clutter. Then it adopts gradual clean algorithm to gradually extract target echoes in the observed region. Furthermore, the detection method based on core vector regression algorithm takes the place of CA-CFAR. Compared with long-time integration detection method, its performance is better and is more suitable to complex signal environment.Finally, the multi-target tracking filtering algorithm based on PHD is analyzed. For the problem of uncorrect extraction of target location information caused by model mismatch, an improved peak extraction algorithm is proposed. Stemmed from the CLEAN algorithm in radar signal processing, it is evidently better than EM algorithm. Furthermore, for the uncertainty of moving target models, a multi-model PHD filtering algorithm is presented. Through parallel data processing of multi-PHD filters, effective tracking is achieved.