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检索条件"主题词=sparsity-based space-time adaptive processing"

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sparsity-based space-time adaptive processing Considering Array Gain/Phase Error

Sparsity-Based Space-Time Adaptive Processing Considering Ar...

引用

CIE International Conference on Radar (RADAR)

作者： Zhu, Yiang Yang, Zhaocheng Huang, Jianjun Shenzhen Univ Coll Informat Engn Shenzhen 518000 Guangdong Peoples R China

ISBN: (纸本)9781509048281

This paper introduces a novel sparsity-based space-time adaptive processing (STAP) considering array gain/phase er-ror (AGPE-STAP) for airborne radar. The proposed AGPE-STAP algorithm combines a conventional sparsity-based STAP method and a conventional array gain/phase error calibration method. The proposed method first models the received returns consider-ing array gain/phase error, estimates the array gain/phase error, calibrates the space-time steering dictionary, and at last designs the filter using the conventional sparsity-based STAP algorithm. Simulation results show that the proposed algorithm outperforms the existing sparsity-based STAP algorithm without calibration in presence of array gain/phase error.

关键词： sparsity-based space-time adaptive processing array gain/phase error calibration airborne radar

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sparsity-based space-time adaptive processing in Random Pulse Repetition Frequency and Random Arrays Radar 13

Sparsity-based Space-Time Adaptive Processing in Random Puls...

引用

13th IEEE International Conference on Signal processing (ICSP)

作者： Quan, Guihua Yang, Zhaocheng Huang, Jianjun Huang, Jinxiong ShenZhen Univ Coll Informat Engn Shenzhen 518000 Peoples R China

ISBN: (纸本)9781509013456

In this paper, we focus on sparsity-based space-time adaptive processing (STAP) in airborne radar with compressive sampling both in Doppler and spatial domains. Compared with the uniform pluses repetition Frequency (UPRF) and uniform arrays (UA) radar, the designed radar transmits random pulse repetition interval pulses and receives the returns with random arrays, which reduces the number of pulses in one coherent processing interval (CPI) and brings down the number of sensors. Firstly, we build the sparse model with spatial-temporal compressive sampling, and analyze the restricted isometry property (RIP) for the steering dictionary. Then, we recover the clutter angle-Doppler profile via existing sparse recovery algorithms, and design the space-time filter to mitigate the clutter. Simulations are conducted to illustrate the effectiveness of the sparsity-based STAP in random PRF and random arrays radar.

关键词： sparsity-based space-time adaptive processing random pulse repetition frequency random arrays compressive sampling restricted isometry property

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sparsity-based space-time adaptive processing in Random Pulse Repetition Frequency and Random Arrays Radar

Sparsity-based Space-Time Adaptive Processing in Random Puls...

引用

2016 IEEE 13th International Conference on Signal processing（ICSP2016）

作者： Guihua Quan Zhaocheng Yang Jianjun Huang Jinxiong Huang College of Information Engineering ShenZhen University College of Information Engineering Shen ZhenUniversity

In this paper, we focus on sparsity-based space-time adaptive processing(STAP) in airborne radar with compressive sampling both in Doppler and spatial domains. Compared with the uniform pluses repetition Frequency(UPRF) and uniform arrays(UA) radar, the designed radar transmits random pulse repetition interval pulses and receives the returns with random arrays, which reduces the number of pulses in one coherent processing interval(CPI) and brings down the number of ***, we build the sparse model with spatial-temporal compressive sampling, and analyze the restricted isometry property(RIP) for the steering dictionary. Then, we recover the clutter angle-Doppler profile via existing sparse recovery algorithms, and design the space-time filter to mitigate the clutter. Simulations are conducted to illustrate the effectiveness of the sparsity-based STAP in random PRF and random arrays radar.

关键词： sparsity-based space-time adaptive processing random pulse repetition frequency random arrays compressive sampling restricted isometry property

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Robust sparsity-based space-time adaptive processing Considering Array Gain/Phase Errors 13

Robust Sparsity-Based Space-Time Adaptive Processing Conside...

引用

13th IEEE International Conference on Signal processing (ICSP)

作者： Zhu, Yiang Yang, Zhaocheng Huang, Jianjun Shenzhen Univ Coll Informat Engn Shenzhen 518000 Guangdong Peoples R China

ISBN: (纸本)9781509013456

This paper proposes a novel robust sparsity-based space-time adaptive processing (STAP) algorithm considering array gain/phase errors for airborne radar. The proposed algorithm builds the sparse signal model considering the array errors, formulates the sparse problem to jointly estimate clutter spatio-temporal profile and the array gain/phase errors, and then designs the space-time adaptive filter based on the reconstructed spatio-temporal profiles. Simulation results show that the proposed algorithm can greatly eliminate the impacts of the array gain/phase errors and improve the output signal-to-interference-noise ratio (SINR) performance.

关键词： robust sparsity-based space-time adaptive processing array gain/phase errors airborne radar

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Robust sparsity-based space-time adaptive processing Considering Array Gain/Phase Errors

Robust Sparsity-Based Space-Time Adaptive Processing Conside...

引用

2016 IEEE 13th International Conference on Signal processing（ICSP2016）

作者： Yiang Zhu Zhaocheng Yang Jianjun Huang College of Information Engineering Shenzhen University

This paper proposes a novel robust sparsity-based space-time adaptive processing(STAP) algorithm considering array gain/phase errors for airborne radar. The proposed algorithm builds the sparse signal model considering the array errors, formulates the sparse problem to jointly estimate clutter spatio-temporal profile and the array gain/phase errors, and then designs the space-time adaptive filter based on the reconstructed spatio-temporal profiles. Simulation results show that the proposed algorithm can greatly eliminate the impacts of the array gain/phase errors and improve the output signal-to-interferencenoise ratio(SINR) performance.

关键词： robust sparsity-based space-time adaptive processing array gain/phase errors airborne radar

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