Widely-linear processing for distributed passive radar systems with strictly non-circular sources

Taghizadeh, Omid; Radhakrishnan, Vimal; Mathar, Rudolf

doi:10.1109/iswcs.2016.7600893

Cited by 1 publication

(3 citation statements)

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“…Furthermore, it enables the FC to customize the appropriate fusion strategy to a specific application, with no need to adapt the optimal operation of the SNs 3 . 2) Estimation Accuracy: As expected, the resulting estimation MSE via the utilization of the LMMSE estimator is always smaller in comparison with the unbiased case, see (17) in comparison with [1, Eq. (21)].…”

Section: ) Optimum Amplification and Power Allocationsupporting

confidence: 57%

“…verifying the known ULMMSE-LMMSE performance gap [22], where MSE unbiased represents the resulting estimation MSE via the application of the optimum ULMMSE fusion, see (17) and (12) in comparison with [1, Eq. (21)].…”

Section: ) Optimum Amplification and Power Allocationmentioning

confidence: 99%

“…The aforementioned works are then extended following a similar optimization strategy, with the consideration of network lifetime and energy efficiency [11]- [14], distributed beamforming among the SNs [15], and occasional node failure and network data inaccuracy [16]. For the sources with strictly non-circular distribution, the gains of a widely linear processing at the SNs, or at the FC is studied in [17].…”

Section: Introductionmentioning

confidence: 99%

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Optimal linear MMSE design for passive distributed radar sensor network systems

Taghizadeh

Radhakrishnan

Alirezaei

et al. 2017

2017 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)

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Abstract-In this paper we present optimal power allocation, together with optimal linear signal fusion, considering a passive distributed radar sensor network system. The goal of a passive distributed radar is to obtain a reliable estimation from a source signal, by collecting and combining the individual observations from the network of sensor nodes (SN)s in a fusion center (FC). In this respect, a linear minimum-mean-square-error (MMSE) optimization strategy is considered, where optimal linear operation at the SNs as well as the FC are obtained analytically. The obtained solutions are then analytically and numerically compared to the previously studied unbiased linear MMSE (ULMMSE) approach. It is observed that both schemes share the same strategy for the optimal power allocation among the SNs, but differ in the corresponding linear fusion. As expected, the proposed approach reaches a lower estimation MSE compared to the ULMMSE one.

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Section: ) Optimum Amplification and Power Allocationsupporting

confidence: 57%

Section: ) Optimum Amplification and Power Allocationmentioning

confidence: 99%