MULTITARGET PARTICLE FILTER BASED TRACK BEFORE DETECT ALGORITHM FOR TRACKING OF SPAWNING TARGETS

Date

2014-04-25

Author

Eyili, Mehmet
Demirekler, Mübeccel

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In this paper, two proposed Track Before Detect (TBD) algorithms for spawning targets on the basis of raw radar measurements are described. These algorithms are developed by using multi-model particle filter method. To improve the efficiency of particle filter a novel reduced order model is introduced. The algorithms are confirmed by using the simulation results and their performances are analyzed on the basis of the probability of target existence and Root Mean Square (RMS) estimation accuracy for very low Signal-to-Noise Ratio (SNR) targets.

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https://hdl.handle.net/11511/52774

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Graduate School of Natural and Applied Sciences, Conference / Seminar

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Multi-target particle filter based track before detect algorithms for spawning targets / Eyili, Mehmet; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2014) In this work, a Track Before Detect (TBD) approach is proposed for tracking and detection of the spawning targets on the basis of raw radar measurements. The principle of this approach is mainly constructed by multi-model particle filter method. In contrast to the related works in the literature, a novel reduced order dynamic model is introduced and the information about bearing angle derived from the radar measurements is not used in this model to improve the efficiency of the particle filter. Moreover, a ...
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Citation Formats

M. Eyili and M. Demirekler, “MULTITARGET PARTICLE FILTER BASED TRACK BEFORE DETECT ALGORITHM FOR TRACKING OF SPAWNING TARGETS,” 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52774.