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When the noises of the linear system are Gaussian white noises with known variances, the optimal state estimation under the minimum mean-square error can be obtained by Kalman filter. However, in the scenario of unknown noise distributions, the estimation accuracy of Kalman filter will be greatly degraded and even diverge. The recursive filtering method is proposed in order to solve this problem. Firstly, the filtering problem is transformed into the quadratic optimization problem with inequality constraints. Secondly, the noise covariances are approximated by the least square method. Then, the recursive minimum mean-square error filtering algorithm without the prior knowledge of system noises is pointed out. Finally, the proposed filtering algorithm is applied to the two-dimensional terminal interception guidance problem. In case of the inaccurate measurements of the line-of-sight angle from the cheaper sensor, the line-of-sight rate is estimated online by this method, and then proportional guidance law is constructed to realize the terminal interception of the lowcost missile against the maneuvering target. The simulation results show that, when compared with Kalman filter, the proposed filter has higher accuracy on the estimation of the line-of-sight rate, thereby improves the guidance and interception performance.
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Basic Information:
DOI：10.16358/j.issn.1009-1300.2021.9.121
China Classification Code:TJ765
Citation Information:
[1]Jin Bingyu,Lu Kelin,Lu Yuping.Recursive Filtering Algorithm with Unknown Noises for Terminal Interception[J].Tactical Missile Technology,2021,No.206(02):55-65.DOI:10.16358/j.issn.1009-1300.2021.9.121.
Fund Information:
国家自然科学基金（61903084）; 江苏省自然科学基金（BK20180358）
2021-03-24
2021-03-24
2021-03-24