可處理多普勒量測的最佳線性無偏估計算法
doi: 10.11999/JEIT141113
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2.
(海軍工程大學理學院 武漢 430033)
基金項目:
國家自然科學基金(51307128, 60873032)，中央高校基本科研業(yè)務費專項資金(2012-Ia-045)，湖北省自然科學基金(2013CFB437)和海工大基金(HJGSK2014G121)資助課題
The Best Linear Unbiased Estimation Algorithm with Doppler Measurements
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1.
(School of Science, Naval University of Engineering, Wuhan 430033, China)
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摘要: 基于目標位置量測的一些量測轉換方法已被廣泛使用在目標跟蹤應用中，使得卡爾曼濾波器得以在直角坐標系中應用。但是，這些量測轉換方法有一些會導致估計性能惡化的根本缺陷。事實上，除了位置量測外，理論計算和實踐已經(jīng)證明，包含目標速度信息的多普勒量測具有有效提高目標狀態(tài)估計精度的潛力。該文在直角坐標系下提出一種可使用轉換多普勒量測(即距離量測與多普勒量測的乘積)的濾波器。從理論上講，它是在最佳線性無偏估計準則下的最優(yōu)線性無偏濾波器，并且避免了量測轉換方法的根本缺陷。通過將近似處理后的新型最優(yōu)線性濾波器與目前4種流行的方法進行仿真比較，驗證了所提出的濾波器的優(yōu)越性。Abstract: A number of measurement-conversion techniques, which are based on position measurements, are widely used in tracking applications, so that the Kalman filter can be applied to the Cartesian coordinates. However, they have fundamental limitations resulting in filtering performance degradation. In fact, in addition to position measurements, the Doppler measurement containing information of target velocity has the potential capability of improving the tracking performance. A filter is proposed which can use converted Doppler measurements (i.e. the product of the range measurements and Doppler measurements) in the Cartesian coordinates. The novel filter is theoretically optimal in the rule of the best linear unbiased estimation among all linear unbiased filters in the Cartesian coordinates, and it is free from the fundamental limitations of the measurement-conversion approach. Based on simulation experiments, an approximate, recursive implementation of the novel filter is compared with those obtained by four state-of-the-art conversion techniques recently. Simulation results demonstrate the effectiveness of the proposed filter.
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