Ambiguity function for distributed MIMO radar systems

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

doi:10.1109/RADAR.2016.7485142

Ambiguity function for distributed MIMO radar systems

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

Electronic And Electrical Engineering

Research output: Contribution to conference › Paper › peer-review

4 Citations (Scopus)

142 Downloads (Pure)

Abstract

In this paper a multi-static ambiguity function (AF) based on the Kullback directed divergence (KDD) and a distributed multiple-input and multiple-output radar system (DMRS) framework is introduced. Additionally a mathematical analysis is used to derive the AF in terms of signal-to-noise ratios (SNRs) and matched filter outputs. This method manages to extract an upper bound and properly define an AF bounded from 0 to 1. Moreover, this method leads in avoidance of large matrices inversions allowing less complex and more accurate computations. Finally the performance of the proposed method in localisation problems is assessed by comparing the proposed AF with the squared summation of the matched filter outputs at each receiver at different SNR scenarios.

Original language	English
Pages	1-6
Number of pages	6
DOIs	https://doi.org/10.1109/RADAR.2016.7485142
Publication status	Published - 2 Jun 2016
Event	IEEE Radar Conference 2016 - Philadelphia, United States Duration: 2 May 2016 → 6 May 2016

Conference

Conference	IEEE Radar Conference 2016
Country/Territory	United States
City	Philadelphia
Period	2/05/16 → 6/05/16

Keywords

multi-static ambiguity function (AF)
distributed multiple-input and multiple-output radar system (DMRS)
kullback directed divergence (KDD)

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10.1109/RADAR.2016.7485142

Ilioudis-etal-RC2016-ambiguity-function-distributed-MIMO-radar-systemsAccepted author manuscript, 692 KB

Signal Processing Solutions for the Networked Battlespace
Soraghan, J. & Weiss, S.
EPSRC (Engineering and Physical Sciences Research Council)
1/04/13 → 31/03/18
Project: Research

Cite this

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title = "Ambiguity function for distributed MIMO radar systems",

abstract = "In this paper a multi-static ambiguity function (AF) based on the Kullback directed divergence (KDD) and a distributed multiple-input and multiple-output radar system (DMRS) framework is introduced. Additionally a mathematical analysis is used to derive the AF in terms of signal-to-noise ratios (SNRs) and matched filter outputs. This method manages to extract an upper bound and properly define an AF bounded from 0 to 1. Moreover, this method leads in avoidance of large matrices inversions allowing less complex and more accurate computations. Finally the performance of the proposed method in localisation problems is assessed by comparing the proposed AF with the squared summation of the matched filter outputs at each receiver at different SNR scenarios.",

keywords = "multi-static ambiguity function (AF), distributed multiple-input and multiple-output radar system (DMRS), kullback directed divergence (KDD)",

author = "Ilioudis, {Christos V.} and Carmine Clemente and Ian Proudler and John Soraghan",

year = "2016",

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doi = "10.1109/RADAR.2016.7485142",

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AU - Ilioudis, Christos V.

AU - Clemente, Carmine

AU - Proudler, Ian

AU - Soraghan, John

PY - 2016/6/2

Y1 - 2016/6/2

N2 - In this paper a multi-static ambiguity function (AF) based on the Kullback directed divergence (KDD) and a distributed multiple-input and multiple-output radar system (DMRS) framework is introduced. Additionally a mathematical analysis is used to derive the AF in terms of signal-to-noise ratios (SNRs) and matched filter outputs. This method manages to extract an upper bound and properly define an AF bounded from 0 to 1. Moreover, this method leads in avoidance of large matrices inversions allowing less complex and more accurate computations. Finally the performance of the proposed method in localisation problems is assessed by comparing the proposed AF with the squared summation of the matched filter outputs at each receiver at different SNR scenarios.

AB - In this paper a multi-static ambiguity function (AF) based on the Kullback directed divergence (KDD) and a distributed multiple-input and multiple-output radar system (DMRS) framework is introduced. Additionally a mathematical analysis is used to derive the AF in terms of signal-to-noise ratios (SNRs) and matched filter outputs. This method manages to extract an upper bound and properly define an AF bounded from 0 to 1. Moreover, this method leads in avoidance of large matrices inversions allowing less complex and more accurate computations. Finally the performance of the proposed method in localisation problems is assessed by comparing the proposed AF with the squared summation of the matched filter outputs at each receiver at different SNR scenarios.

KW - multi-static ambiguity function (AF)

KW - distributed multiple-input and multiple-output radar system (DMRS)

KW - kullback directed divergence (KDD)

U2 - 10.1109/RADAR.2016.7485142

DO - 10.1109/RADAR.2016.7485142

M3 - Paper

SP - 1

EP - 6

T2 - IEEE Radar Conference 2016

Y2 - 2 May 2016 through 6 May 2016

ER -

Ambiguity function for distributed MIMO radar systems

Abstract

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Keywords

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Signal Processing Solutions for the Networked Battlespace

Cite this