Study On Cognitive Radar Waveform And Stagger Filtering Optimization Algorithm

Cognitive radar is an important developing direction of the radar in the future. Itcan adaptively adjust launch waveform and working mode by the prior knowledge ofenvironment, and make full use of information for intelligent processing, and effectivelyimprove the performance of the radar, which work in the increasingly complicatedenvironment. For cognitive radar, waveform optimal design and stagger-codeoptimizations are presented in this dissertation.For the waveform optimization with the cognitive ability, the transmitter adjuststhe transmitting signal by using the priori information, which the receiver feedbacks tothe transmitter, to achieve optimal matching of transmitting signal and environment. Aset of orthogonal phase-coded signals are obtained based on the genetic algorithm, andset up waveform library. When transmitting signal is intercepted by enemy, theappropriate signal can be jumped to another transmitting signal according to thecognitive strategies. The performance analysis demonstrates the efficiency of theorthogonal phase-coded as agile signal to suppress interference.Under the clutter background, stagger MTI filter design algorithm is proposed inthe dissertation, based on the cognitive ability of Doppler velocity, to improve the weaktarget detection performance. By this algorithm multi-model clutters can be effectivelysuppressed, blind speeds of spectrum can be appeared out of three times as velocity ofsound as, and the target’s power loss is as small as possible when the known targetDoppler frequency is constrained, so the weak target can be detected effectively. Theoptimization stagger code is obtained by genetic algorithm.