Research On Waveform Optimization Design For Cognitive Radar Target Detection

As a remote sensing system,radar can detect and identify targets and is widely used in battlefield environments.The waveform emitted by the radar is an important tool for interaction with the environment,and the quality of the waveform parameters has an important impact on the performance of the radar.Compared with traditional radars that can only transmit relatively fixed waveforms,cognitive radars can extract information from the echo environment to form a transceiver feedback loop,adaptively adjust the waveform sent by the transmitter to adapt to the detection environment,and improve the performance of the radar system.Cognitive radar has attracted a lot of attention in the radar field due to its flexibility and adaptability.This paper studies the waveform optimization algorithm of cognitive radar system.Firstly,the method of establishing the objective function of cognitive radar waveform optimization is studied from the two aspects of radar detection environment state and design criteria.In view of the situation that modern radars undertake multiple tasks at the same time,a waveform optimization method based on adaptive joint optimization criteria is proposed.This method is based on the signal-to-noise ratio criterion and mutual information criterion,and according to the priority of radar target detection and recognition tasks.The criteria are adjusted adaptively to meet the requirements of waveform optimization design even when the task changes dynamically.The simulation results show that the waveform design based on the adaptive joint optimization criterion can optimize the transmission waveform in different tasks and is more adaptable than other criteria.Secondly,the cognitive radar waveform optimization algorithm when the target information is missing is studied.In the absence of target information,using the closed-loop feedback structure of cognitive radar,the paper first maximizes the output signal-to-noise ratio of the receiver’s generalized matched filter through sequential estimation,and studies the radar waveform design based on the joint optimization of transceivers.On this basis,the target information estimation error is further considered,and an adaptive filter-based transceiver joint optimization method is designed.The radar’s detection performance of targets under different target transmission coefficients and transmission signal lengths is simulated and analyzed.The simulation results show that.This method has good detection performance under target reflection coefficient and transmitted signal length,and can be applied to different radar environments.Finally,the optimization of radar waveform transmission under jamming targets is studied.Aiming at the situation that the jamming target also has the ability to recognize in the modern complex confrontation environment,the paper studies the radar waveform design based on game theory.First,the problem of selecting the waveform of radar and target is studied under the matrix game model.Aiming at the problem of low average radar return,an iterative-Brown algorithm based on feedback mechanism is proposed to improve radar detection performance by adjusting the average return of strategy,Aiming at whether the information of the two parties is symmetrical,the waveform parameter optimization based on the Nash equilibrium(NE)game and the Stackelberg equilibrium(SE)game are studied respectively.The simulation results show that NE is superior to SE in terms of radar detection performance,but the disadvantage is that it has more iterations.The realization of NE needs to meet the condition of symmetry of information between the two parties,and SE can be used to approximate replacement when the conditions are insufficient.