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在多雷达数据处理系统中,影响目标跟踪和数据融合质量的一个重要因素是雷达系统偏差。为了使融合结果更加准确可靠,提出了基于无偏转换的雷达误差配准算法。该算法是通过无偏转换把其它雷达的测量转换到主雷达下,利用各雷达相对主雷达的测量差值,采用Kalman滤波器实时估计出各雷达的系统偏差(方位和距离),从而进行配准。仿真实验结果表明这种算法是有效的。
In a multi-radar data processing system, one important factor that affects the quality of target tracking and data fusion is the radar system bias. In order to make the fusion result more accurate and reliable, a radar error registration algorithm based on unbiased conversion is proposed. The algorithm transforms the measurements of other radars to the primary radar through unbiased conversion. The Kalman filter is used to estimate the system deviation (azimuth and distance) of each radar in real time by using the measurement difference of each radar relative to the primary radar quasi. Simulation results show that this algorithm is effective.