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机构地区:[1]中国电子科技集团公司第三十八研究所,安徽合肥230088
出 处:《雷达科学与技术》2013年第3期271-275,280,共6页Radar Science and Technology
摘 要:当机载ESM定位系统的干涉仪的基线长度较短,传统的相位差变化率无源定位方法很难取得满意的定位效果,所以结合机载ESM传感器的特点,提出了基于方位角的迭代最小二乘定位算法,然后用Kalman滤波对迭代最小二乘对固定辐射源估计结果进行优化,当方位角比较大时,可以通过坐标旋转变换来提高了该算法的定位性能。Monte-Carlo仿真及结果分析进一步说明该算法具有收敛速度快,有效张角大,定位精度高,更具鲁棒性的特点。通过分析,该算法在军事应用中具有很好的前景。The traditional passive location using phase rate of change is very difficult to achieve satisfactory results when the interferometer baseline length of airborne ESM location system is short. Therefore, a recursive least-squares(RLS) location algorithm based bearing measurement is presented. The Kalman filter is applied to optimize the location results of the fixed emitter estimated by the RLS. The performance of the algorithm is greatly enhanced by coordinate rotation transform when the azimuth is large. Monte Carlo simu- lations and result analysis further prove that the presented algorithm has many advantages, such as high precision, quick location, large opening angle and more robust. It may has good prospect in military applications.
关 键 词:机载ESM传感器 无源定位 相位差变换率 迭代最小二乘 KALMAN滤波
分 类 号:TN971[电子电信—信号与信息处理]
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