Translational motion estimation with multistatic ISAR systems

Testa, Alejandro; Santi, Fabrizio; Pastina, Debora

doi:10.23919/irs51887.2021.9466180

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…this line were previously described in [17,18]. The proposed decentralized multistatic technique estimates the kinematic parameters via a two-step procedure: (1) first estimate the single-sensor signal parameters (Doppler centroid and Doppler rate); (2) then jointly exploit the estimated signal parameters to estimate the kinematic of the target.…”

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confidence: 99%

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

Testa,

Pastina,

Santi

2023

Remote Sensing

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This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application.

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confidence: 99%

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

Testa,

Pastina,

Santi

2023

Remote Sensing

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Distributed ISAR imaging based on convolution and total variation reweighted l ₁ regularization

Fu,

Wang,

et al. 2024

International Journal of Remote Sensing

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Comparing decentralized and centralized approaches for translational motion estimation with multistatic ISAR systems

Testa

Pastina

Santi

2022

2022 23rd International Radar Symposium (IRS)

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Translational motion estimation with multistatic ISAR systems

Cited by 3 publications

References 11 publications

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

Distributed ISAR imaging based on convolution and total variation reweighted l ₁ regularization

Comparing decentralized and centralized approaches for translational motion estimation with multistatic ISAR systems

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Translational motion estimation with multistatic ISAR systems

Cited by 3 publications

References 11 publications

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

Distributed ISAR imaging based on convolution and total variation reweighted l 1 regularization

Comparing decentralized and centralized approaches for translational motion estimation with multistatic ISAR systems

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Distributed ISAR imaging based on convolution and total variation reweighted l ₁ regularization