超声速弱目标二维频域检测与参数估计算法

Detection and Parameter Estimation Algorithm for Supersonic Weak Targets in 2-D Frequency Domain

超声速弱目标在长积累时间内会发生严重的距离走动,导致常规雷达检测性能急剧下降,针对该问题,本文提出了一种超声速弱目标二维频域检测与参数估计算法。首先给出了超声速弱目标回波信号模型,并分析了距离走动特性。在此基础上,推导了超声速弱目标回波二维频域表达式,得出了距离频域和方位频域存在线性关系的结论,并根据二维频域中的斜线进行积累,以此提高目标的检测性能,同时完成目标的参数估计。最后,通过仿真实验分析了该算法的检测和参数估计性能,理论推导和仿真结果表明该算法的信噪比积累增益为脉压比和相参积累脉冲数的乘积。

The range walk of supersonic weak targets is a serious problem in the long coherent integration time. And the traditional radar has poor detection performance on the targets of this type. To solve the problem, a detection and parameter estimation algorithm for the supersonic weak targets in the two dimensional （2-D） frequency domain is proposed in the pa- per. First the echo signal model of supersonic weak targets is presented, and the characteristic of range walk is analyzed. Based on this, the expression of the echo in the 2-D frequency domain is derived, and the linear relation between range fre- quency and azimuth frequency is concluded. Then integration along the slanted line in the 2-D frequency domain is per- formed to improve the detection performance of the targets and their parameters are estimated simultaneously. Finally, the performance of target detection and parameter estimation of the algorithm are analyzed by the simulation experiments, and theoretical derivation and simulation results suggest that the signal-to-noise ratio（SNR） integration gain of the algorithm is the product of pulse compression ratio and pulse number of coherent integration.