DOA Tracking Via Signal-Subspace Projector Update

Zhuang, Jie; Tan, Tianhan; Chen, Daolin; Kang, Jiancheng

doi:10.1109/icassp40776.2020.9054122

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…Coherent Processing Interval (CPI), during which multiple snapshots can be collected, e.g. [9], [10]. Target tracking in this environment can be achieved through localisation.…”

Section: Notationsmentioning

confidence: 99%

MIMO Radar: An H-Infinity Approach for Robust Multitarget Tracking in Unknown Cluttered Environment

Liu,

Manikas

2024

IEEE Trans. Aerosp. Electron. Syst.

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In Multiple-Input Multiple-Output (MIMO) radar, adaptive multi-target tracking can be achieved using subspace tracking algorithms in conjunction with super-resolution subspace localisation algorithms. However, the presence of unknown radar clutter deteriorates or breaks algorithms that rely on the white noise assumption. In this paper, an H ∞ approach is proposed for robust tracking of each target's range, Direction of Arrival (DOA) and velocity with unknown clutter. Specifically, Doppler SpatioTemporal ARray (Doppler-STAR) and virtual Doppler-STAR manifold extenders are first proposed by combining the slow-time and fast-time dimensions of a pulse MIMO radar received signal. Then, in the 'extended' space, H ∞ adaptive filtering is used to track a noise subspace equivalent, which exists regardless of the noise assumption. Finally, the target parameters are extracted from the adaptively tracked noise subspace. Based on computer simulation studies, the performance of the proposed H ∞ tracking approach is evaluated using challenging tracking scenarios and compared against several existing subspace tracking algorithms.

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“…Coherent Processing Interval (CPI), during which multiple snapshots can be collected, e.g. [9], [10]. Target tracking in this environment can be achieved through localisation.…”

Section: Notationsmentioning

confidence: 99%

MIMO Radar: An H-Infinity Approach for Robust Multitarget Tracking in Unknown Cluttered Environment

Liu,

Manikas

2024

IEEE Trans. Aerosp. Electron. Syst.

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Subspace tracking for time-varying direction-of-arrival estimation with sensor arrays

Liao

Zhang

Chan

2022

IoT and Spacecraft Informatics

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Underwater Acoustic Localization Based on IR-GCC-PHAT in Reverberant Environments

Yoshizawa

2021

International Journal of Circuits, Systems and Signal Processing

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This paper presents a method of underwater acoustic localization in reverberant environments. Time difference of arrival (TDOA) measurement algorithm is a key technology for estimating direction of arrival (DOA) of an underwater sound source. In strong multipath interference, the pseudo-peaks in a correlation function disturb the detection of a correct time position and lead to a large TDOA measurement error. The proposed algorithm computes a time difference by taking cross-correlation of two impulse responses and improves robustness to multipath interference. The comparison of TDOA algorithms is done by evaluating the position accuracy of underwater sound source in both simulation and experiment.

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DOA Tracking Via Signal-Subspace Projector Update

Cited by 4 publications

References 20 publications

MIMO Radar: An H-Infinity Approach for Robust Multitarget Tracking in Unknown Cluttered Environment

MIMO Radar: An H-Infinity Approach for Robust Multitarget Tracking in Unknown Cluttered Environment

Subspace tracking for time-varying direction-of-arrival estimation with sensor arrays

Underwater Acoustic Localization Based on IR-GCC-PHAT in Reverberant Environments

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