基于遗传算法的雷达组网误差配准算法

系统误差校正是雷达组网的关键问题，传统的误差校正方法采用最小均方估计法或极大似然法，这些方法受随机误差影响，计算量大，难以在工程中应用。本文在实时精度控制法（RTOC）的基础上，通过构造误差配准的目标函数，将误差配准转换为非线性优化问题，并采用遗传算法进行寻优。该方法采用非参数化的方法进行误差配准，克服了RTOC和最小二乘算法中线性化带来的误差，提高了误差估计的精度。仿真和实际数据测试表明，本文提供的方法能有效地进行组网雷达误差配准。

Registration Algorithm for Radar Netting Based on Genetic Algorithm

The registration is a key problem in radar netting. Traditionally, the least square（LS） method or maximum likelihood method, which are sensitive to noise and difficult to be calculated, are used to solve this problem. In this paper, a new method based on genetic algorithm is discussed. In this method, the error registration is transformed into a nonlinear optimization problem by constructing the target function, then it can be solved by use of genetic algorithm. This algorithm conquers the error due to linearization in the realtime quality control（RTOC） and LS and improves the precision of error registrar＇Ion. At last, this paper gives simulated and actual data. The results indicate that this algorithm can improve the accuracy of plot and track fusion and is a effectual way to registration error of radar netting.