认知雷达的未知目标检测

认知雷达可以在探测过程中不断优化自身系统参数，实现与当前探测环境的匹配，从而能够改善雷达的探测性能。针对未知目标的探测问题，利用当前回波数据更新目标分量的估计值及其协方差矩阵，基于目标相关信息优化下一次探测所需的发射机波形和接收机滤波器，并构成一个闭环处理过程。该文提出了两种优化途径，第1种途径利用目标分量的估计仅优化下一次探测波形，在接收端采用广义匹配滤波器；第2种途径将估计误差等效为信号依赖的噪声，联合优化发射波形与接收机滤波器。计算机仿真分析表明，采用闭环迭代优化的方法是渐进等效的，并可以在相干累积获得的性能增益基础上，进一步改善雷达的探测性能。

Unknown Target Detection for Cognitive Radar

For the cognitive radar system, the system parameters can be optimized to match the current environment during the detection procedure, so as to improve the radar detection performance. For the unknown target detection problem, the useful signal component estimate and its covariant matrix are updated using the current returns, then the transmit waveform and receive filter are optimized based on the information of the useful signal. A closed loop processing is formed. The two optimization approaches are proposed. For the first approach, the transmit waveform design is based on the estimate of the useful signal, and the generalized match filter is used at the receiver. For the second approach, the estimate error of the useful signal is equivalent to the signal- dependent noise, and the transmit waveform and receive filter are jointly designed. The computer simulation result show that, the proposed methods are asymptotically equivalent, and they can improve the detection performance further, compared with the performance gain of the coherent accumulation.