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.

Decentralized approach for translational motion estimation with multistatic inverse synthetic aperture radar systems / Testa, Alejandro; Pastina, Debora; Santi, Fabrizio. - In: REMOTE SENSING. - ISSN 2072-4292. - 15:18(2023), pp. 1-28. [10.3390/rs15184372]

Decentralized approach for translational motion estimation with multistatic inverse synthetic aperture radar systems

Alejandro Testa
;
Debora Pastina;Fabrizio Santi
2023

Abstract

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.
2023
inverse synthetic aperture radar; translational motion estimation; multistatic radar systems
01 Pubblicazione su rivista::01a Articolo in rivista
Decentralized approach for translational motion estimation with multistatic inverse synthetic aperture radar systems / Testa, Alejandro; Pastina, Debora; Santi, Fabrizio. - In: REMOTE SENSING. - ISSN 2072-4292. - 15:18(2023), pp. 1-28. [10.3390/rs15184372]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1689231
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