The Direct Position Determination (DPD) algorithm can offer higher estimation accuracy, but is accompanied by serious computation load. To solve this problem, this paper proposes a novel DPD algorithm based on Modified Cubature Kalman Filter (MCKF). First, a direct positioning filtering model based on the direction of arrival information of the received signals is developed with the subspace data fusion method. Then, an MCKF is proposed to solve the problem of noise accumulation caused by indirect observation. Finally, the computational complexity of the algorithm is analyzed to illustrate its efficiency. Simulation results show that compared with the DPD algorithms based on maximum likelihood exhaustive search and genetic algorithm, the proposed algorithm can significantly reduce computation load and improve timeliness while maintaining the same estimation accuracy, showing great applicability in practice.
LU Zhiyu
,
WANG Jianhui
,
BA Bin
,
WANG Daming
. Direct position determination algorithm based on modified cubature Kalman filter[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018
, 39(9)
: 322031
-322038
.
DOI: 10.7527/S1000-6893.2018.22031
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