Dynamic programming track-before-detect algorithm for radar target detection based on polynomial time series prediction

An improved dynamic programming track-before-detect (DP-TBD) algorithm is proposed in this study. A new relaxed DP-TBD test statistic containing a term of state transition probability is derived. The state transition probability is designed according to the one-step prediction of the target state. A...

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Vydáno v:	IET radar, sonar & navigation Ročník 10; číslo 8; s. 1327 - 1336
Hlavní autoři:	Zheng, Daikun, Wang, Shouyong, Meng, Qingwen
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 01.10.2016
Témata:	Algorithms Dynamic programming energy back‐scattered integration improved dynamic programming track‐before‐detect algorithm Mathematical models object detection polynomial time series prediction Polynomials Radar detection radar target detection regression analysis relaxed DP‐TBD test statistic Research Article state transition probability Statistical tests Time series Transition probabilities weighted least squares radar detection improved dynamic programming track-before-detect algorithm polynomials regression analysis weighted least squares dynamic programming time series object detection state transition probability radar target detection relaxed DP-TBD test statistic polynomial time series prediction energy back-scattered integration
ISSN:	1751-8784, 1751-8792
On-line přístup:	Získat plný text
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