ISAR imaging based on improved phase retrieval algorithm

doi:10.21629/JSEE.2018.02.08

Abstract

Abstract:

Traditional inverse synthetic aperture radar (ISAR) imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed, which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler (RD) algorithm and oversampling smoothness (OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.

Key words: inverse synthetic aperture radar (ISAR), maneuvering target, autofocus imaging, phase retrieval, oversampling smoothness (OSS)

Hongyin SHI, Saixue XIA, Ye TIAN. ISAR imaging based on improved phase retrieval algorithm[J]. Journal of Systems Engineering and Electronics, 2018, 29(2): 278-285.

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Parameter	Symbol	Value
Target's initial position in range/km	$ R_{0} $	16
Target's rotational velocity/(rad/s)	w	0.02
Starting frequency/GHz	$ f_{0} $	9
Frequency bandwidth/MHz	B	125
Pulse repetition frequency/KHz	PRF	35
Number of pulses	$ N_{\rm pulse} $	128
Number of bursts	$ M_{\rm burst} $	128

Algorithm	Iteration	Success rate
Classical OSS algorithm	200	0.11
Classical OSS algorithm	500	0.12
The proposed algorithm	200	1
The proposed algorithm	500	1

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