基于归一化互相关的系统误差配准算法

雷达组网中由于系统误差存在,航迹不能正确关联,因而无法进行有效的误差配准。为了解决这一问题,理论分析了系统误差对目标航迹的影响并将该影响表示为目标航迹的旋转和平移量,结合图像信号时频域特性,提出了一种基于归一化互相关的误差配准算法。该算法采用归一化互相关来估计和补偿组网雷达目标航迹到融合中心航迹的相对旋转参数和平移参数,从而为后面的系统误差配准提供可靠的航迹关联数据。

A Bias Registration Algorithm Based on Normalized Cross-Correlation

Bias error has often brought about inaccurate track correlation; say noting of accurate registration in radar network. In order to solve the problem, firstly, it was analyzed that how did the bias errors affect the detected track of targets, and the effect caused by bias errors was expressed as some rotation and translation parameters. Secondly, with the time-frequency feature of image signal, a bias pre-registration algorithm based on cross-correlation had been presented. The algorithm estimations and compensates the rotation and translation parameters by normalized cross-correlation, and aligns the track data of targets provided by radars in the network to which of the fusion center, so the algorithm can provide reliable associated tracks for the later registration.