Joint underwater target detection and tracking with the Bernoulli filter using an acoustic vector sensor
Küçük Resim Yok
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Academic Press Inc Elsevier Science
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we study the problem of joint underwater target detection and tracking using an acoustic vector sensor (AVS). For this challenging problem, first a realistic frequency domain simulation is set up. The outputs of this simulation generate the two dimensional FRequency-AZimuth (FRAZ) image. On this image, the random finite set (RFS) framework is employed to characterize the target state and sensor measurements. We propose to use the Bernoulli filter, which is the optimal Bayes filter emerged from the RFS framework for randomly on! off switching single dynamic systems. Moreover, to increase the performance of detection and azimuth tracking in low signal-to-noise ratio (SNR) scenarios, a track-before-detect (TBD) measurement model for AVS is proposed to be used with the Bernoulli filter. Sequential Monte Carlo (SMC) implementation is preferred for the Bernoulli filter recursions. Extensive simulation results prove the performance gain obtained by the proposed approach both in estimation accuracy and detection range of the system. (C) 2015 Elsevier Inc. All rights reserved.
Açıklama
Anahtar Kelimeler
Acoustic vector sensor; The Bernoulli filter; Random finite sets; Target tracking; Track before detect
Kaynak
Digital Signal Processing
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
48
