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针对纯方位系统下扩展卡尔曼滤波等递推算法性能不稳定,最小二乘定位算法计算量大、实时性差的特点,提出了一种改进的最小二乘定位算法。该算法根据目标与平台之间的几何关系得到一个包含目标初始位置和分量速度的伪线性方程组。为减少求解方程组的计算量,保证定位的实时性,对常规的最小二乘法进行了加滑窗处理,并进一步将方程组的解表示为递推形式。仿真实验验证了算法的有效性,并比较了平台做不同机动运动的定位性能,给出了满足一定精度时平台的机动策略。
Aiming at the unstable performance of recursive algorithm such as extended Kalman filter in purely azimuth system and the large amount of computation and the poor real-time performance of least squares positioning algorithm, an improved least squares positioning algorithm is proposed. According to the geometric relationship between the target and the platform, the algorithm obtains a pseudo-linear system of equations that contains the initial position of the target and the component velocity. In order to reduce the computational complexity of solving equations and ensure the real-time performance of positioning, the conventional least-squares method is added with sliding window processing, and the solution of the system of equations is further expressed as a recursive form. The simulation results show the effectiveness of the algorithm. The platform is compared with the positioning performance of different maneuvering motions and the maneuvering strategy of the platform is given.