Localization of harmonic source using a single moving sensor of known trajectory

Ang, Yi Yang; Nguyen, Nam; Lie, Joni Polili; Gan, Woon Seng

doi:10.1109/apsipa.2017.8282045

Cited by 3 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the minimum part in (21), if θ ki = θ kℓ then the minimum is zero and for the maximum part, we demonstrate the following Theorem.…”

Section: A Framework For Path Optimizationmentioning

confidence: 69%

“…With respect to Corollary 1, we expect that two cells that placed next to each other have the minimum changes in phase interval (21). Now suppose that the i th and j th cells are located next to each other.…”

Section: A Framework For Path Optimizationmentioning

confidence: 99%

“…A category of techniques suggests to employ a moving platform to pursue passive source localization or direction finding. In [21], using a moving sensor, a large synthetic aperture antenna is formed to localize a simple harmonic source. In another work, a co-prime sampled large aperture array is employed to passively localize PUs [22].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Wireless Source Localization Utilizing An Airborne Interfrometry

Hejazi¹,

Joneidi²,

Rahnavard³

2021

Preprint

View full text Add to dashboard Cite

This paper investigates the problem of localization of co-channel transmitters or primary users (PUs) using an array mounted on a moving aerial platform. As a practical alternative for a sensor network to pursue the localization task, the proposed Phase Interferometric Source Localization (PISL) technique utilizes a moving sensor that measures phase difference between two antennas mounted on the platform. Due to the sparse nature of PUs' distribution in the region, we model the localization task as a simple basis-pursuit denoising framework and introduce a reconstruction method using a sparse recovery algorithm to discover locations of unknown PUs based on the phase difference measurements. We show that the ratio of distance between two antennas to the carrier-frequency wavelength is the critical parameter making the localization feasible. We also propose a scheme for sensor motion design in order to maximize the number of detectable PUs based on mutual coherence property. Since the motion optimization problem is very hard to address we develop a simple geometric relaxation to address the problem. The simulation results show that PISL can precisely recover the map of PUs with only few measurements and also reveal that sensor motion path can have determinate effect on the localization accuracy. PISL performance is compared with an state-of-the-art technique that utilizes adaptive beamforming and results show the superiority of PISL results in localization accuracy.

show abstract

“…For the minimum part in (21), if θ ki = θ kℓ then the minimum is zero and for the maximum part, we demonstrate the following Theorem.…”

Section: A Framework For Path Optimizationmentioning

confidence: 69%

Section: A Framework For Path Optimizationmentioning

confidence: 99%