基于合作目标与非合作目标的一体化空间配准新算法

针对移动平台雷达同时探测到合作目标与非合作目标怎样进行空间配准的问题，提出了一种一体化的空间配准算法，将基于合作目标的雷达系统偏差估计结果作为附加条件输入到基于非合作目标建立的线性方程组中，一起采用递推最小二乘法（RLS）重新估计两平台的系统偏差大小。仿真结果表明该新方法切实可行，合理地利用了合作目标信息与共同量测的非合作目标信息，提高了雷达量测系统偏差估计的准确性和最终目标航迹的配准精度，相信在多机协同探测领域具有一定的应用价值。

A new algorithm of space registration using cooperative and noncooperative targets

To solve the space registration problem of simultaneous radar measurements of cooperative and noncooperative targets, a new algorithm is proposed in which the bias estimation result based on cooperative targets is used as the additional input of the linear equations constructed from the common noncooperative targets. The system biases of both radars, including those having detected cooperative targets and those not, are estimated with recursive least squares(RLS) method. The computer simulation shows that the proposed algorithm can use the measurement information of two types of targets effectively and can improve the system bias estimation and the registered track precision greatly. It is believed that the algorithm has values in region of multi-sensor cooperative detections.