WU Weihua, JIANG Jing, FENG Xun, QIN Xing. A Sequential Converted Measurement Kalman Filter with Doppler Measurements in ECEF Coordinate System[J]. Chinese Journal of Electronics, 2016, 25(1): 139-145. doi: 10.1049/cje.2016.01.021
Citation: WU Weihua, JIANG Jing, FENG Xun, QIN Xing. A Sequential Converted Measurement Kalman Filter with Doppler Measurements in ECEF Coordinate System[J]. Chinese Journal of Electronics, 2016, 25(1): 139-145. doi: 10.1049/cje.2016.01.021

A Sequential Converted Measurement Kalman Filter with Doppler Measurements in ECEF Coordinate System

doi: 10.1049/cje.2016.01.021
Funds:  This work is supported by the National Natural Science Foundation of China (No.61102168).
  • Received Date: 2014-01-03
  • Rev Recd Date: 2014-09-04
  • Publish Date: 2016-01-10
  • When there is the correlation between Doppler and slant range, previous literatures have presented some sequential filter algorithms. However, they are only applied to simplified fixed radar' s local coordinate system. As a result, a Sequential converted measurement Kalman filter (SCMKF) with Doppler measurements based on the Earth centered earth fixed (ECEF) coordinate system applicable to a moving airborne platform which has time varying attitude is proposed. Firstly, the correlated Doppler and range are decorrelated using the Cholesky factorization, then the converted position measurements are obtained by a series of coordinate transformation with unchanged range component and other observations, such as azimuth and elevation angles; the corresponding error covariances are derived which are used to the Converted measurement Kalman filter (CMKF). Finally the sequential filter is implemented for changed pseudo-Doppler measurements. The proposed method is validated through Monte Carlo test compared with the performance of CMKF with just converted position measurements and traditional SCMKF with Doppler which ignores the correlation between Doppler and range noises, and the conclusion is obtained that utilizing Doppler information correctly can improve tracking performance, nevertheless, the improvement gain of filter accuracy is limited, which can provide some references for engineering application.
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