NDLI: A novel unscented filter TBD algorithm FOR weak radar target

Content Provider	IEEE Xplore Digital Library
Author	Yu Hongbo Wang Guohong Cao Qian
Copyright Year	2013
Description	Author affiliation: Inst. of Inf. Fusion, Naval Aeronaut. & Astronaut. Univ., Yantai, China (Yu Hongbo; Wang Guohong) \|\| Libr., Naval Aeronaut. & Astronaut. Univ., Yantai, China (Cao Qian)
Abstract	In this paper, the unscented particle filter (UPF) is adopted to realize the tracking before detection (TBD) of weak radar target. In order to construct an accurate approximation to true proposal distribution, the state at each time scan is predicted according to the unscented Kalman filter (UKF). Unfortunately, in the framework of TBD, the UPF is used to handle with the raw measurements, which are unthresholded. In this situation, how to select the only measurement to compute the innovation is an important and difficult issue. Thus, it is difficult to perform the state update, and ineffective selection will lead to poor performance or even fail to detect targets. To address this problem, a modified UPF-TBD algorithm (MUPF-TBD) is proposed, in which the observation innovation is generated by a dummy observation. And the dummy observation can be generated from the measurement prediction of the state estimation at last step. Thus, using the feedback information, this new proposed method can obtain an accurate approximation to the system and as a result, improve the estimation performance. An application example is given to draw a comparison between this new algorithm and the existing algorithm. Simulation results illustrate the effectiveness of this approach.
Starting Page	1
Ending Page	5
File Size	384307
Page Count	5
File Format	PDF
ISBN	9781479910274
DOI	10.1109/ICSPCC.2013.6664078
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Technological innovation Target tracking Radar detection Dummy observation Weak radar target Radar tracking Particle measurements Particle filters Unscented particle filter Tracking before detection
Content Type	Text
Resource Type	Article

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