Abstract
In inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, such as ships fluctuating with oceanic waves and high maneuvering airplanes, the multi-component quadratic frequency modulation (QFM) signals are more suitable model for azimuth echo signals. The quadratic chirp rate (QCR) and chirp rate (CR) cause the ISAR imaging defocus. Thus, it is important to estimate QCR and CR of multi-component QFM signals in ISAR imaging system. The conventional QFM signal parameter estimation algorithms suffer from the cross-term problem. To solve this problem, this paper proposes the product high order ambiguity function-modified integrated cubic phase function (PHAF-MICPF). The PHAF-MICPF employs phase differentiation operation with multi-scale factors and modified coherently integrated cubic phase function (MICPF) to transform the multi-component QFM signals into the time-quadratic chirp rate (T-QCR) domains. The cross-term suppression ability of the PHAF-MICPF is improved by multiplying different T-QCR domains that are related to different scale factors. Besides, the multiplication operation can improve the anti-noise performance and solve the identifiability problem. Compared with high order ambiguity function-integrated cubic phase function (HAF-ICPF), the simulation results verify that the PHAF-MICPF acquires better cross-term suppression ability, better anti-noise performance and solves the identifiability problem.
Highlights
The high-resolution inverse synthetic aperture radar (ISAR) has played an important role in civil and military fields in past decades [1]
The cross-term suppression ability of the PHAF-modified coherently integrated cubic phase function (MICPF) is improved by multiplying different T-quadratic chirp rate (QCR) domains that are related to different scale factors
We propose the PHAF-MICPF to estimate QCR and chirp rate (CR) of quadratic frequency modulation (QFM) signal
Summary
The high-resolution inverse synthetic aperture radar (ISAR) has played an important role in civil and military fields in past decades [1]. It suffers from the cross-term problem when multi-component QFM signals exist and it has poor estimation performance under low signal-to-noise ratio (SNR). A new approach for QFM signal parameters estimation named product high order ambiguity function-modified integrated CPF (PHAF-MICPF) is proposed for multi-QFM signals. This algorithm employs a one-time phase differentiation operation that has multi-scale factors to demodulate the QFM signal to LFM signal. The proposed algorithm employs the modified ICPF (MICPF) to transform the demodulated LFM signal into the time-quadratic chirp rate (T-QCR) domains, which are related to the scale factors.
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