Multiple Carrier Agile Radar via Compressed Sensing

Tianyao Huang; Y. Liu; Yonina C. Eldar; X. Wang

Multiple Carrier Agile Radar via Compressed Sensing

Tianyao Huang, Y. Liu, Yonina C. Eldar, X. Wang

Department of Computer Science and Applied Mathematics

Weizmann Institute of Science

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

Abstract

Frequency agile radar (FAR) is known to have excellent electronic counter-countermeasure performance [1]. Recently, compressed sensing (CS) based algorithms have been developed for joint range and Doppler estimation in FAR. To further improve the reconstruction performance, this paper suggests a waveform based on FAR, which we refer to as multiple carrier agile radar (MCAR). In MCAR, multiple carriers are transmitted in each pulse. The mutual coherence of the measurement matrix of MCAR is analyzed, and is shown to be better than the counterpart of FAR. Numerical simulations also demonstrate the performance improvement of MCAR over traditional FAR using CS techniques in terms of probabilities of successful recovery.

Original language	English
Number of pages	5
State	Published - Sep 2018
Event	Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), - University City of Siegen, Germany, Siegen, Germany Duration: 10 Sep 2018 → 13 Sep 2018

Conference

Conference	Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa),
Abbreviated title	CoSeRa
Country/Territory	Germany
City	Siegen
Period	10/09/18 → 13/09/18

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https://www.eurasip.org/Proceedings/Ext/CoSeRa2018/papers/p-huang.pdf

Cite this

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title = "Multiple Carrier Agile Radar via Compressed Sensing",

abstract = "Frequency agile radar (FAR) is known to have excellent electronic counter-countermeasure performance [1]. Recently, compressed sensing (CS) based algorithms have been developed for joint range and Doppler estimation in FAR. To further improve the reconstruction performance, this paper suggests a waveform based on FAR, which we refer to as multiple carrier agile radar (MCAR). In MCAR, multiple carriers are transmitted in each pulse. The mutual coherence of the measurement matrix of MCAR is analyzed, and is shown to be better than the counterpart of FAR. Numerical simulations also demonstrate the performance improvement of MCAR over traditional FAR using CS techniques in terms of probabilities of successful recovery.",

author = "Tianyao Huang and Y. Liu and Eldar, {Yonina C.} and X. Wang",

note = "NA; Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), ; Conference date: 10-09-2018 Through 13-09-2018",

year = "2018",

month = sep,

language = "الإنجليزيّة",

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TY - CONF

T1 - Multiple Carrier Agile Radar via Compressed Sensing

AU - Huang, Tianyao

AU - Liu, Y.

AU - Eldar, Yonina C.

AU - Wang, X.

N1 - NA

PY - 2018/9

Y1 - 2018/9

N2 - Frequency agile radar (FAR) is known to have excellent electronic counter-countermeasure performance [1]. Recently, compressed sensing (CS) based algorithms have been developed for joint range and Doppler estimation in FAR. To further improve the reconstruction performance, this paper suggests a waveform based on FAR, which we refer to as multiple carrier agile radar (MCAR). In MCAR, multiple carriers are transmitted in each pulse. The mutual coherence of the measurement matrix of MCAR is analyzed, and is shown to be better than the counterpart of FAR. Numerical simulations also demonstrate the performance improvement of MCAR over traditional FAR using CS techniques in terms of probabilities of successful recovery.

AB - Frequency agile radar (FAR) is known to have excellent electronic counter-countermeasure performance [1]. Recently, compressed sensing (CS) based algorithms have been developed for joint range and Doppler estimation in FAR. To further improve the reconstruction performance, this paper suggests a waveform based on FAR, which we refer to as multiple carrier agile radar (MCAR). In MCAR, multiple carriers are transmitted in each pulse. The mutual coherence of the measurement matrix of MCAR is analyzed, and is shown to be better than the counterpart of FAR. Numerical simulations also demonstrate the performance improvement of MCAR over traditional FAR using CS techniques in terms of probabilities of successful recovery.

M3 - محاضرة

T2 - Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa),

Y2 - 10 September 2018 through 13 September 2018

ER -

Multiple Carrier Agile Radar via Compressed Sensing

Abstract

Conference

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