ISAR Imaging of Maneuvering Target Based on the Local Polynomial Wigner Distribution and Integrated High-Order Ambiguity Function for Cubic Phase Signal Model

2014 ◽  
Vol 7 (7) ◽  
pp. 2971-2991 ◽  
Author(s):  
Yong Wang ◽  
Jian Kang ◽  
Yicheng Jiang
Keyword(s):  
Wigner Distribution ◽  
Ambiguity Function ◽  
High Order ◽  
Cubic Phase ◽  
Signal Model ◽  
Maneuvering Target ◽  
Local Polynomial ◽  
Isar Imaging ◽  
Phase Signal

scholarly journals Quadratic Frequency Modulation Signals Parameter Estimation Based on Product High Order Ambiguity Function-Modified Integrated Cubic Phase Function

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 140 ◽  
Author(s):  
Lei Zhu
Keyword(s):  
Phase Function ◽  
Imaging System ◽  
Ambiguity Function ◽  
High Order ◽  
Cubic Phase ◽  
Chirp Rate ◽  
Cross Term ◽  
Isar Imaging ◽  
Identifiability Problem ◽  
Cubic Phase Function

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.

A New Maneuvering Target Detection Algorithm in OTHR

2014 ◽  
Vol 644-650 ◽  
pp. 1122-1125
Author(s):  
Hui Yong Li ◽  
Wan Ge Li ◽  
Jin Feng Hu ◽  
Hui Ai ◽  
Zhi Rong Lin
Keyword(s):  
Target Detection ◽  
Signal To Noise Ratio ◽  
Order Reduction ◽  
Detection Algorithm ◽  
Doppler Spectrum ◽  
Cubic Phase ◽  
Maneuvering Target ◽  
Phase Signal ◽  
Motion Parameters ◽  
Noise Ratio

In the three-order polynomial phase signal, HAF can be used to reduce phase order to achieve the phase parameter estimation. The loss of signal to noise ratio in the order reduction processing is serious. In order to reduce the SNR loss, this paper uses CPF to reduce phase order. It requiers two one-dimensional searches to estimate the rate of acceleration and acceleration. The estimated motion parameters are used to compensate the target echo doppler and doppler spectrum expansion can be suppressed. This paper proposes a new maneuvering target detection algorithm with low non-linearity. The algorithm makes use of the cubic phase function (CPF) to estimate target motion parameters and reduce the number of phase order. Simulation demonstrates the effectiveness of the proposed algorithm and the adaptability to low signal noise ratio.

ISAR Imaging of a Maneuvering Target Based on Parameter Estimation of Multicomponent Cubic Phase Signals

2021 ◽  
pp. 1-18
Author(s):  
Penghui Huang ◽  
Xiang-Gen Xia ◽  
Muyang Zhan ◽  
Xingzhao Liu ◽  
Guisheng Liao ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Cubic Phase ◽  
Maneuvering Target ◽  
Isar Imaging
Sign in / Sign up

Export Citation Format

Share Document