Generalised ambiguity function for MIMO radar systems

Christos V. Ilioudis; Carmine Clemente; Ian Proudler; John Soraghan

doi:10.1109/TAES.2019.2907390

Generalised ambiguity function for MIMO radar systems

Christos V. Ilioudis, Carmine Clemente, Ian Proudler, John Soraghan

Electronic And Electrical Engineering

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

64 Downloads (Pure)

Abstract

In this work a generalised signal model is presented to accommodate both narrowband and wideband signals in a multi-input multi-output (MIMO) sensor system scenarios. The derived model is then used to define a MIMO ambiguity function (AF) based on the Kullback-Leibler divergence (KLD). Moreover, the proposed formulation is parametrised using the signal and channel correlation matrices to account for different waveform and sensor placement designs, thereby allowing a flexible modelling approach. A comparison between the proposed definition and the more conventional approach of summing the squared matched filter outputs is presented for different sensors and waveforms configurations.

Original language	English
Number of pages	16
Journal	IEEE Transactions on Aerospace and Electronic Systems
Early online date	2 Apr 2019
DOIs	https://doi.org/10.1109/TAES.2019.2907390
Publication status	E-pub ahead of print - 2 Apr 2019

Keywords

multiple input multiple output systems
MIMO AF
multiple input multiple output ambiguity function
Kullback-Leibler divergence

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10.1109/TAES.2019.2907390

Ilioudis-etal-IEEE-TAES-2019-Generalised-ambiguity-function-for-MIMO-radarAccepted author manuscript, 6.07 MB

Cite this

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abstract = "In this work a generalised signal model is presented to accommodate both narrowband and wideband signals in a multi-input multi-output (MIMO) sensor system scenarios. The derived model is then used to define a MIMO ambiguity function (AF) based on the Kullback-Leibler divergence (KLD). Moreover, the proposed formulation is parametrised using the signal and channel correlation matrices to account for different waveform and sensor placement designs, thereby allowing a flexible modelling approach. A comparison between the proposed definition and the more conventional approach of summing the squared matched filter outputs is presented for different sensors and waveforms configurations.",

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AU - Clemente, Carmine

AU - Proudler, Ian

AU - Soraghan, John

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N2 - In this work a generalised signal model is presented to accommodate both narrowband and wideband signals in a multi-input multi-output (MIMO) sensor system scenarios. The derived model is then used to define a MIMO ambiguity function (AF) based on the Kullback-Leibler divergence (KLD). Moreover, the proposed formulation is parametrised using the signal and channel correlation matrices to account for different waveform and sensor placement designs, thereby allowing a flexible modelling approach. A comparison between the proposed definition and the more conventional approach of summing the squared matched filter outputs is presented for different sensors and waveforms configurations.

AB - In this work a generalised signal model is presented to accommodate both narrowband and wideband signals in a multi-input multi-output (MIMO) sensor system scenarios. The derived model is then used to define a MIMO ambiguity function (AF) based on the Kullback-Leibler divergence (KLD). Moreover, the proposed formulation is parametrised using the signal and channel correlation matrices to account for different waveform and sensor placement designs, thereby allowing a flexible modelling approach. A comparison between the proposed definition and the more conventional approach of summing the squared matched filter outputs is presented for different sensors and waveforms configurations.

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KW - Kullback-Leibler divergence

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Generalised ambiguity function for MIMO radar systems

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Signal Processing Solutions For the Networked Battlespace

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Generalised ambiguity function for MIMO radar systems

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