Please use this identifier to cite or link to this item: https://doi.org/10.1155/2017/8723042
Title: Micromotion Feature Extraction of Space Target Based on Track-Before-Detect
Authors: Chen, Y
Zhang, Q
Luo, Y
Yeo, T.S 
Keywords: Extraction
Radar
Space-based radar
Target tracking
Tracking radar
Effective approaches
Feature extraction methods
Feature parameters
State transitions
Target detecting
Target detection and tracking
Target recognition
Track before detect
Feature extraction
Issue Date: 2017
Citation: Chen, Y, Zhang, Q, Luo, Y, Yeo, T.S (2017). Micromotion Feature Extraction of Space Target Based on Track-Before-Detect. Journal of Sensors 2017 : 8723042. ScholarBank@NUS Repository. https://doi.org/10.1155/2017/8723042
Rights: Attribution 4.0 International
Abstract: The micromotion feature of space target provides an effective approach for target recognition. The existing micromotion feature extraction is implemented after target detection and tracking; thus the radar resources need to be allocated for target detection, tracking, and feature extraction, successively. If the feature extraction can be implemented by utilizing the target detecting and tracking pulses, the radar efficiency can be improved. In this paper, by establishing a feedback loop between micromotion feature extraction and track-before-detect (TBD) of target, a novel feature extraction method for space target is proposed. The TBD technology is utilized to obtain the range-slow-time curves of target scatterers. Then, micromotion feature parameters are estimated from the acquired curve information. In return, the state transition set of TBD is updated adaptively according to these extracted feature parameters. As a result, the micromotion feature parameters of space target can be extracted concurrently with implementing the target detecting and tracking. Simulation results show the effectiveness of the proposed method. @ 2017 Yijun Chen et al.
Source Title: Journal of Sensors
URI: https://scholarbank.nus.edu.sg/handle/10635/179548
ISSN: 1687725X
DOI: 10.1155/2017/8723042
Rights: Attribution 4.0 International
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