Frequency-Agile Radar Signal Processing

Waters, William M.; Linde, G.

doi:10.1109/taes.1979.308841

Cited by 16 publications

(7 citation statements)

References 4 publications

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“…where e n denotes the nth element of e, ⊙ indicates Hardmard product. Because of the constant module constraint of e, we can find ϵ 2 ¼ kwk 2 2 ¼ ke � ⊙ wk 2 2 . By introducing the auxiliary variable vector b, Equation (26) converts to min a kak 1 s:t:…”

Section: Joint Phase Error Estimation and Sparse Scene Restoration Algorithm Based On Admmmentioning

confidence: 99%

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Joint phase error estimation and sparse scene restoration algorithms for frequency agile radar

Fei

Zhang

Zhu

et al. 2021

IET Radar Sonar & Navi

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Frequency agile radar (FAR) systems have been demonstrated to have outstanding performance in electronic counter-countermeasures (ECCM). With increased bandwidth in which FAR can switch carrier frequency, the phase errorswill appear at the corresponding frequency point, resulting in the decrease of coherence of the system. To accomplish phase error correction and range and velocity information extraction of the target simultaneously, a joint phase error estimation and sparse scene restoration algorithm based on sparse recovery (JPSA-SR) is proposed here. To further reduce the computational complexity of the algorithm, a joint phase error estimation and sparse scene restoration algorithm based on alternating direction method of multipliers (JPSA-ADMM) is also proposed. Numerical examples show the effectiveness of the proposed algorithms.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Section: Joint Phase Error Estimation and Sparse Scene Restoration Algorithm Based On Admmmentioning

confidence: 99%

“…This means the requirement of the full coherence of the FAR systems can be relaxed. (2) The proposed algorithms are constructed based on sparse recovery and alternating direction method of multipliers. Sparse recovery has been demonstrated to have the capability to suppress the high sidelobe in coherent integration.…”

Section: Introductionmentioning

confidence: 99%

Joint phase error estimation and sparse scene restoration algorithms for frequency agile radar

Fei

Zhang

Zhu

et al. 2021

IET Radar Sonar & Navi

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“…This technique has already been exploited among radar and general radio applications to account for jamming or adverse atmospheric conditions [25]. Acoustic domains can also take advantage of this idea, as it has the potential to accomplish sound processing at the periphery of the sensor system by exploiting feedback coupling between mechanical and electrical processes at the transducer level (e.g.…”

Section: B Future Work Towards Frequency Agility In Acoustic Sensorsmentioning

confidence: 99%

Simple Ears Inspire Frequency Agility in an Engineered Acoustic Sensor System

2017

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Abstract-Standard microphones and ultrasonic devices are generally designed with a static and flat frequency response in order to address multiple acoustic applications. However, they may not be flexible or adaptable enough to deal with some requirements. For instance, when operated in noisy environments such devices may be vulnerable to wideband background noise which will require further signal processing techniques to remove it, generally relying on digital processor units. In this work, we consider if microphones and ultrasonic devices could be designed to be sensitive only at selected frequencies of interest, whilst also providing flexibility in order to adapt to different signals of interest and to deal with environmental demands. This research exploits the concept where the "transducer becomes part of the signal processing chain" by exploring feedback processes between mechanical and electrical mechanisms that together can enhance peripheral sound processing. This capability is present within a biological acoustic system, namely in the ears of certain moths. That was used as the model of inspiration for a smart acoustic sensor system which provides dynamic adaptation of its frequency response with amplitude and time dependency according to the input signal of interest.

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“…Instead, each pulse at center frequency ω CM (m) is coherently added to the corresponding pulse frequency at a PRI-delay of T. In this way, M simultaneous coherent processing intervals can be constructed. The advantage of this approach is that M independent, frequency agile looks at the moving target are provided for reduction of target scintillation effects, and improvement in target location accuracy [3]. A disadvantage is that there is range eclipsing at each sub-pulse PRI.…”

Section: A Waveformmentioning

confidence: 99%

“…A conservative estimate of this SNR improvement is 2 dB, when comparing a Swerling 0 target to a Swerling 2 [3].…”

Section: Detailed Modeling Approachmentioning

confidence: 99%

Common waveform for simultaneous SAR and GMTI

Davis¹,

Kapfer

Bozek

2011

2011 IEEE RadarCon (RADAR)

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Surveillance RADARs normally share time for detecting fixed and moving targets. With modern digital waveform synthesis and high performance computing, it is feasible to collect signals that use space, time and frequency encoding to simultaneously operate in GMTI and SAR modes. This paper summarizes a new waveform and adaptive RADAR architecture with the potential for simultaneous SAR and GMTI operation, along with a detailed simulation of target detections.

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Frequency-Agile Radar Signal Processing

Cited by 16 publications

References 4 publications

Joint phase error estimation and sparse scene restoration algorithms for frequency agile radar

Joint phase error estimation and sparse scene restoration algorithms for frequency agile radar

Simple Ears Inspire Frequency Agility in an Engineered Acoustic Sensor System

Common waveform for simultaneous SAR and GMTI

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