The Technology For Small Target Detection In Complex Background

Modern radar is not only affected by various clutter,but also suffers from strong electromagnetic interference,which makes the working environment of radar very complex.In addition,with the rapid development of the technology for unmanned aerial vehicle and stealth,the radar cross section(RCS)of the target becomes smaller and smaller.The combination of these two factors leads to the serious deterioration of radar detection performance.The algorithm of signal processing is the key to improve the radar performance without changing the radar hardware.To solve the defects of the traditional methods,this thesis studies the traditional radar signal processing methods and proposes some optimized algorithms to improve the performance of small target detection in complex environment.Firstly,this thesis introduces the principles of pulse compression(PC)matched filtering,and analyzes the effects of discrete sampling error on S-shaped nonlinear frequency modulation signal(NLFM)pulse compression.Based on the practical project,an optimization method with respect to the S-shaped NLFM is proposed,in which the problem of echo mismatches is assessed.Under the sampling frequency commonly used in the practical system,it is possible to reduce the impact of discrete sampling error on the pulse compression results and improve the mainlobe-to-sidelobe ratio(MSR)effectively.Then,the method of clutter suppression is studied.Some filter design methods of moving target indication(MTI)and moving target detection(MTD)for clutter suppression are introduced in detail after presenting the clutter model.The clutter suppression performance of various filters is analyzed through simulation experiments.Next,the radar target detection algorithm is studied,which introduces a multi-channel clutter map detection method.Based on the phase information,the ultra-low speed target be detected in the clutter background,which effectively avoids the phenomenon of self-shadowing.In addition,four constant false alarm rate(CFAR)detectors are introduced,and the detection performance and CFAR detection loss in various environments are analyzed through simulation experiments.Subsequently,the ambiguities of range and velocity resulted from the pulse Doppler system are explained,and then the defects of the traditional methods resolving ambiguities resolution are analyzed.Based on above problems,a method of resolving the range ambiguity is proposed,which is based on the coherent accumulation with jitter repetition frequency.Then,a method of resolving velocity ambiguity based on the coherent accumulation with stagger repetition frequency.These two methods can make full use of radar pulse resources,which improves the signal-to-noise ratio(SNR)by 3d B and makes it possible for radar to detect the small targets and resolve their ambiguities effectively.Finally,the estimation of the direction of arrival(DOA)in the frequency agile phased array radar is studied,which analyzes the accumulation methods with multiple noncoherent snapshots.Then,a maximum likelihood angle measurement method for the frequency agile phase array radar is proposed based on the optimal fusion.The proposed method can effectively accumulate multiple snapshots by optimally weighting the angle estimation values of multiple snapshots.Caused by the fluctuation of SNR,the performance losses in the frequency agile phase array radar is avoided and the accuracy of angle estimation is thus improved.Even in the low SNR,the angle measurement accuracy can also be improved.