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Angle Estimation Error Reduction Method Using Weighted IMM and Least Squares

Seong Hee Choi, Taek Lyul Song*
International Journal of Control, Automation, and Systems, vol. 15, no. 1, pp.354-361, 2017

Abstract : "This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM."

Keyword : Angle estimation error, interacting multiple model, least squares, weighted interacting multiple model.

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