信号相关杂波环境中的认知雷达多扩展目标跟踪

摘要

研究了相关杂波和多目标环境下的认知雷达目标跟踪问题.提出了基于贝叶斯思想,具有迭代循环结构的认知雷达跟踪系统框架.在该框架下,基于卡尔曼滤波实现了对多个扩展目标的跟踪,并且通过优化波形的方法提高了多目标跟踪性能.在波形优化中,为提高跟踪性能,分别从量测、信干噪比和状态更新误差角度出发设计了相应的最优波形.仿真结果表明:基于所提出的框架,雷达以高估计精度实现了对多个目标的跟踪,且所设计波形的跟踪性能均优于传统的固定波形.%The problem of cognitive radar tracking in the signal-dependent clutter and multi-target environment is considered.The framework of cognitive radar tracking which has the iterative cycle structure is proposed based on Bayesian idea.In this framework,the tracking of multiple targets is implemented by Kalman filter,and the tracking performance is improved by waveform optimization.For improving the tracking performance,three waveforms are designed based on the measurement noise optimization,signal-to-interference-and-noise rate optimization and state update error optimization respectively.The simulation results indicate that the multiple targets are tracking precisely by the proposed framework,and the tracking performance of these designed waveforms are better than that of fixed waveform which is used widely in traditional radar.