In this paper, we consider a distributed passive radar with non-cooperative illuminators of opportunity (IOs) operating on non-overlapping frequency bands and tackle the problem of direct target localization. Assuming that each passive radar receiver employs reference channels to measure the direct-path signals from the IOs and a surveillance channel to collect the target echoes corrupted by the direct-path interference (DPI), we derive the maximum likelihood estimator of the target position through the joint estimation of unknown parameters. This estimator reveals the masking effect of DPI on the target echoes and achieves joint DPI suppression and target position estimation. To reduce the large computational complexity of this estimator caused by a lack of knowledge of the IO signals, a suboptimal estimator is then devised by separately processing the observations from the reference and surveillance channels to sequentially estimate the unknown parameters. As a benchmark, we also derive the corresponding Cramér-Rao Lower Bound (CRLB) on the estimation error of the target position. Finally, an extensive numerical analysis is provided to assess the performance of the proposed suboptimal estimator in single- and multi-target scenarios, also in comparison with other estimators that ignore the DPI at the design stage and/or assume prior knowledge of the IO signals. Remarkably, the proposed estimator is robust against the DPI and can provide a localization accuracy close to the CRLB in practical operating conditions.

Direct Target Localization for Distributed Passive Radars With Direct-Path Interference Suppression

Venturino, Luca;
2024-01-01

Abstract

In this paper, we consider a distributed passive radar with non-cooperative illuminators of opportunity (IOs) operating on non-overlapping frequency bands and tackle the problem of direct target localization. Assuming that each passive radar receiver employs reference channels to measure the direct-path signals from the IOs and a surveillance channel to collect the target echoes corrupted by the direct-path interference (DPI), we derive the maximum likelihood estimator of the target position through the joint estimation of unknown parameters. This estimator reveals the masking effect of DPI on the target echoes and achieves joint DPI suppression and target position estimation. To reduce the large computational complexity of this estimator caused by a lack of knowledge of the IO signals, a suboptimal estimator is then devised by separately processing the observations from the reference and surveillance channels to sequentially estimate the unknown parameters. As a benchmark, we also derive the corresponding Cramér-Rao Lower Bound (CRLB) on the estimation error of the target position. Finally, an extensive numerical analysis is provided to assess the performance of the proposed suboptimal estimator in single- and multi-target scenarios, also in comparison with other estimators that ignore the DPI at the design stage and/or assume prior knowledge of the IO signals. Remarkably, the proposed estimator is robust against the DPI and can provide a localization accuracy close to the CRLB in practical operating conditions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/110026
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