Target vibration estimation in SAR based on phase-analysis method

Weijie Xia,Linlin Huang

doi:10.1186/s13634-016-0390-7

Abstract

An efficient vibration estimation method for synthetic aperture radar (SAR) systems based on phase-analysis method is presented. Small vibrations, which consist of multiple frequency components and are usually rather weak, introduce phase modulation in radar echoes. They contain important signatures of objects. Extracting and analyzing the phase from radar echoes is one of the significant approaches to acquire vibration characteristics. In order to separate different targets in different range cells, the proposed method acts the range compression and range migration correction on the radar echoes, followed by extracting the phase history of each target’s radar echoes. Since the phase history contains the time-varying ranges from the targets to airborne radar besides the vibration signal, we apply wavelet transform to the phase history to extract the vibration signal. Then the vibration signatures would be estimated quantitatively. The method is a more efficient and convenient approach to estimate the vibration amplitudes and frequencies of one or more targets, whose vibration signal is a single-frequency or multi-frequency signal. Moreover, it can be applied in the case where the airborne radar moves along the desirable or undesirable trajectory. Simulation results indicate that this method provides a larger range of estimable vibration frequency, higher estimation precision, and lower computation complexity.

Highlights

Vibration is ubiquitous in the real world
Spaceborne synthetic aperture radar (SAR) can operate over thousands of kilometers, which is an effective way to acquire vibration signatures of structures placed in remote locations
Adding a zero-mean complex-valued white Gaussian noise to every SAR return, we compute normalized root-mean-square error (NRMSE) to evaluate the performance of the proposed method in estimating the vibration signal under different signal-to-noise ratio (SNR) levels

Summary

Introduction

Vibration is ubiquitous in the real world. Objects’ vibration signatures bear vital information about the type of the objects [1]. This expression demonstrates that the phase of the range line is the sum of two parts: − 4πf0 ⋅ r(η)/c, which is linear proportional to the nominal line-of-sight distance from the target to the radar sensor and − 4πf0 ⋅ rv0(η)/c The former varies slowly with azimuth time referred to as a low-frequency signal. Adding a zero-mean complex-valued white Gaussian noise to every SAR return, we compute NRMSEs to evaluate the performance of the proposed method in estimating the vibration signal under different SNR levels. The real phase was acquired by the method proposed, which consists of two components: the variation with azimuth time of the nominal line-of-sight distance from the target to the radar sensor and the vibration signal, which are referred to as the low-frequency signal and the highfrequency signal, respectively.

Airborne radar along undesirable trajectory

Conclusions