GLRT Particle Filter for Tracking Nlos Target in Around-the-Corner Radar

Thai, Khac-Phuc-Hung; Rabaste, Olivier; Bosse, Jonathan; Chonavel, Thierry

doi:10.1109/icassp.2018.8462391

Cited by 7 publications

(9 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The target position is determined by using scene transfer Green's function involving different multipath reflection and corner diffraction propagation paths [21], and by the intersection of two circles, which are related to the first-order multipath reflection path and the diffraction path [22], respectively. A generalized likelihood ratio test particle filter for the problem of tracking a single NLOS target in around-the-corner radar is considered in [23]. A scanning, narrow beam radar system and a method are proposed to locate NLOS targets behind a corner in [24].…”

Section: Behind Corner Targets Location Using Smallmentioning

confidence: 99%

Behind Corner Targets Location Using Small Aperture Millimeter Wave Radar in NLOS Urban Environment

Guo

Zhao

Cui

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

It is often difficult to detect the targets of interest via the line-of-sight (LOS) signals in the urban environment, since the LOS signals might be not available because of the presence of the walls. This article considers the target positioning problem via non-LOS signals using the single-input multiple-output small aperture millimeter wave radar. Assume that a target is located around a building corner and the geometric structure is known a priori. The phase comparison based algorithm is proposed, by exploiting the multipath propagation of the electromagnetic wave and the phase differences of the echoes among multiple channels. Finally, we validate the proposed algorithm via real data. Index Terms-Urban environment, NLOS multipath propagation signals, SIMO millimeter wave radar, target positioning. I. INTRODUCTION T HE detection of the targets in the urban environment is of great interests in the military and the civil security fields such as the urban battle, the antiterrorism, the disaster rescue, and the law enforcement arrest [1]-[6]. Unlike conventional radars, the line-of-sight (LOS) signals are often not available because of the presence of the walls. Hence, the targets detection via non-LOS (NLOS) signals has received considerable attention [7]-[22]. These works can be divided into two types with respect to the penetrating signals and the NLOS multipath propagation signals. The first type utilizes the penetrating signal. The propagation path of electromagnetic (EM) wave will be changed due to the refraction when passing through the walls, which will results in several problems such as the target position shift and image defocus. In [8]-[10], three wall parameters estimation methods

show abstract

Section: Behind Corner Targets Location Using Smallmentioning

confidence: 99%

Behind Corner Targets Location Using Small Aperture Millimeter Wave Radar in NLOS Urban Environment

Guo

Zhao

Cui

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

show abstract

“…It is worthwhile to integrate this additional information into the particle filter framework with the aim of reducing the weight of ghost position particles, then improving the estimation results. Both simulated and experimental results obtained with the proposed multiple receiving antenna particle filter show that it can achieve higher convergence rate and robustness compared to single antenna-based tracking [10], thus better localization results.…”

Section: Introductionmentioning

confidence: 97%

“…To deal with this problem, called localization ambiguity in [7], the authors of [10] adopted the tracking approach, for instance using the particle filter. The simple idea behind is to exploit the dynamics of the target over several radar measurements to remove the ghost positions which are not relevant and are not belonging to the target track.…”

Section: Introductionmentioning

confidence: 99%

“…The use of a particle filter was justified by the high non-linearity of the measurement model [11], since multipath radar parameters are linked to the target position states by unknown and complex geometrical relations that are specific to each scenario. Moreover, the Generalized Likelihood Ratio Test (GLRT) particle filter algorithm, first introduced in [12] in the Track-Before-Detect framework, has been chosen for implementation in [10]. It is designed to circumvent the disadvantages of sampling multipath amplitude by replacing it with its ML estimator.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

GLRT Particle Filter for Non-Line of Sight Single Moving Target Tracking via Phased Array Radar

Pham,

Rabaste,

Bosse

et al. 2023

2023 26th International Conference on Information Fusion (FUSION)

Self Cite

View full text Add to dashboard Cite

In around the corner radar, particle filter tracking can help to improve the estimation accuracy of a Non-Line of Sight target position. However, in case of using one single receiving antenna, the measurement model only contains multipath delay information. Due to the lack of information in the model, particles corresponding to ambiguous positions can be assigned high weight values. This can leads the particle cloud to diverge from the actual target trajectory and requires several time steps to converge on it again. In this work, our proposed solution consists in exploiting additional Direction-of-Arrival information provided by an array of receiving antennas in the particle filter framework. By simulation and experimentation, we will show that the proposed solution allows to solve the aforementioned problem, and thus achieves better localization results compared to single antenna-based tracking as well as non-tracking localization algorithm.

show abstract

“…In [16], a target position estimation algorithm based on multipath tracking of first-order reflection path was proposed. In [17], the generalized likelihood ratio test particle filter is employed to provide the most efficient NLOS targets localization results. In [18] and [19], Thai et al carried out the work of detecting and locating targets in NLOS areas with a single portable radar by exploiting reflection multipath.…”

Section: Introductionmentioning

confidence: 99%

On the Electromagnetic Diffraction Propagation Model and Applications

Cui

Guo

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Detection and localization of nonline-of-sight (NLOS) hidden target in complex urban environment is a very recent radar detection problem. In this article, we investigate the possibility of locating a target in a building corner NLOS region with a single-input single-output ultra-wideband radar by exploring the electromagnetic (EM) diffraction propagation path. The EM wave diffraction phenomenon referring to this single rectangular corner of the building is analyzed and the diffraction model in this scenario is established. Assuming that the geometric structure of the scenario is known earlier, we introduce an application of the destination location behind the corner based on the propagation of the EM wave diffraction. Finally, the numerical simulation and real data results demonstrate that a micromotion target and moving target can be localized exploiting the proposed approach. Index Terms-Electromagnetic (EM) diffraction propagation, nonline-of-sight (NLOS) signal, target localization, urban environment, ultra-wideband (UWB) radar.

show abstract

GLRT Particle Filter for Tracking Nlos Target in Around-the-Corner Radar

Cited by 7 publications

References 7 publications

Behind Corner Targets Location Using Small Aperture Millimeter Wave Radar in NLOS Urban Environment

Behind Corner Targets Location Using Small Aperture Millimeter Wave Radar in NLOS Urban Environment

GLRT Particle Filter for Non-Line of Sight Single Moving Target Tracking via Phased Array Radar

On the Electromagnetic Diffraction Propagation Model and Applications

Contact Info

Product

Resources

About