Joint Detection and DOA Tracking with a Bernoulli Filter Based on Information Theoretic Criteria.

Guangpu Zhang, Ce Zheng, Sibo Sun, Guolong Liang, Yifeng Zhang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

DOA Tracking Based on Unscented Transform Multi-Bernoulli Filter in Impulse Noise Environment.Sensors (Basel, Switzerland) · 2019
Article

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Guangpu ZhangAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China. zhangguangpu@hrbeu.edu.cn.

Ce ZhengAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China. zhengce_uae@hrbeu.edu.cn.ORCID 0000-0002-3569-2700

Sibo SunAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China. sunsibo@hrbeu.edu.cn.ORCID 0000-0002-2728-4934

Guolong LiangAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China. liangguolong@hrbeu.edu.cn.

Yifeng ZhangAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China. zhangyifeng1@hrbeu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we study the problem of the joint detection and direction-of-arrival (DOA) tracking of a single moving source which can randomly appear or disappear from the surveillance volume. Firstly, the Bernoulli random finite set (RFS) is employed to characterize the randomness of the state process, i.e., the dynamics of the source motion and the source appearance. To increase the performance of the detection and DOA tracking in low signal-to-noise ratio (SNR) scenarios, the measurements are obtained directly from an array of sensors and allow multiple snapshots. A track-before-detect (TBD) Bernoulli filter is proposed for tracking a randomly on/off switching single dynamic system. Secondly, since the variances of the stochastic signal and measurement noise are unknown in practical applications, these nuisance parameters are marginalized by defining an uninformative prior, and the likelihood function is compensated by using the information theoretic criteria. The simulation results demonstrate the performance of the filter.

Indexed as

Bernoulli filterDOAtrack before detect

Identifiers

PMID30326658

DOI10.3390/s18103473

PMCPMC6210454

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.