An Improved Target Tracking Algorithm Based on Extended Kalman Filter for UAV

被引：0

作者：

Li, Yibing ^{[1
]}

Jiu, Mingyang ^{[1
]}

Sun, Qian ^{[1
]}

Wang, Yansong ^{[2
]}

机构：

[1] Coll Informat & Commun Engn, Harbin, Peoples R China

[2] State Radio Monitoring Ctr, Harbin Monitoring Stn, Harbin, Peoples R China

来源：

PROCEEDINGS OF THE 2018 IEEE 7TH ASIA-PACIFIC CONFERENCE ON ANTENNAS AND PROPAGATION (APCAP) | 2018年

基金：

中国国家自然科学基金;

关键词：

EKF; optimization; sudden maneuver; target tracking; errors of location;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

With the sudden maneuver produced by a target, Extended Kalman Filter (EKF) will produce a non-ignored error. Then the sensor's observation range may be exceeded. In order to solve this problem, an optimization for target tracking based on EKF is proposed in this paper, exploiting sliding window to monitor the innovations to detect whether EKE has diverged and a modified EKF with expanding dimension model considering acceleration jerk is considered to be practicable to continue the algorithm instead. Simulation results are presented comparing EKE to improved EKE in different conditions and illustrating the feasibility and availability of the improved EKF.

引用

页码：435 / 437

页数：3

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