A Fast Motion Parameters Estimation Method Based on Cross-Correlation of Adjacent Echoes for Wideband LFM Radars

Zhang, Yixiong; Hong, Ru-Jia; Yang, Cheng-Fu; Zhang, Yunjian; Deng, Zhenmiao; Sheng, Jin

doi:10.20944/preprints201704.0090.v1

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…Literature [3] proposed another traditional motion compensation method to solve the nonlinear phase relationship in the Bi‐ISAR system, which did not apply to sparse aperture. Literature [15] proposed a fast non‐parametric search method based on the cross‐correlation of adjacent echoes, which calculated the motion parameters by estimating the frequency of the correlation results. Despite its good estimation performance, the correlation of adjacent echoes is reduced under sparse aperture conditions, rendering it inapplicable.…”

Section: Introductionmentioning

confidence: 99%

A bistatic inverse synthetic aperture radar sparse aperture high‐resolution imaging algorithm with migration compensation

Zhu

Guo

et al. 2022

IET Radar Sonar & Navi

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In recent years, bistatic inverse synthetic aperture radar (Bi‐ISAR) imaging of targets with sparse aperture has attracted more and more attention. One of the critical issues is that the Bi‐ISAR imaging of some large targets with rotational motions is prone to migration through resolution cells, which increases the imaging difficulty. In order to enhance the compensation for through resolution cell migration in those scenarios and improve the accuracy and resolution of Bi‐ISAR images under sparse aperture, that is, improving the target recognition of Bi‐ISAR, the authors aimed at the high‐order migration term and the high‐order phase error term and proposed a Bi‐ISAR sparse aperture high‐resolution imaging algorithm based on complex Bayesian compressed sensing and frequency resampling. The algorithm was solved by ‘distributed’ iteration. The migration compensation under the sparse aperture conditions was completed, and the quality of the reconstructed images was improved. Simulation results verified the effectiveness and superiority of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

A bistatic inverse synthetic aperture radar sparse aperture high‐resolution imaging algorithm with migration compensation

Zhu

Guo

et al. 2022

IET Radar Sonar & Navi

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“…In recent years, numerous researchers have explored the parameter estimation problem of chirp signals from different aspects [1], [9], [12]- [22]. Inspired by the recentlydeveloped sparse reconstruction method [23]- [28], we propose a fast and high accuracy parameter estimation method for LFM signals in the FrFD based on orthogonal matching pursuit (OMP).…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of Fractional Bandlimited LFM Signals Based on Orthogonal Matching Pursuit

Wang

Luo

2019

IEICE Trans. Fundamentals

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Parameter estimation theorems for LFM signals have been developed due to the advantages of fractional Fourier transform (FrFT). The traditional estimation methods in the fractional Fourier domain (FrFD) are almost based on two-dimensional search which have the contradiction between estimation performance and complexity. In order to solve this problem, we introduce the orthogonal matching pursuit (OMP) into the FrFD, propose a modified optimization method to estimate initial frequency and final frequency of fractional bandlimited LFM signals. In this algorithm, the differentiation fractional spectrum which is used to form observation matrix in OMP is derived from the spectrum analytical formulations of the LFM signal, and then, based on that the LFM signal has approximate rectangular spectrum in the FrFD and the correlation between the LFM signal and observation matrix yields a maximal value at the edge of the spectrum (see Sect. 3.3 for details), the edge spectrum information can be extracted by OMP. Finally, the estimations of initial frequency and final frequency are obtained through multiplying the edge information by the sampling frequency resolution. The proposed method avoids reconstruction and the traditional peak-searching procedure, and the iterations are needed only twice. Thus, the computational complexity is much lower than that of the existing methods. Meanwhile, Since the vectors at the initial frequency and final frequency points both have larger modulus, so that the estimations are closer to the actual values, better normalized root mean squared error (NRMSE) performance can be achieved. Both theoretical analysis and simulation results demonstrate that the proposed algorithm bears a relatively low complexity and its estimation precision is higher than search-based and reconstruction-based algorithms.

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“…Maneuvering-target tracking using laser, radar, and/or sonar is essential for monitoring systems in robots, aircrafts, and intelligent vehicles. For some applications in such technical fields, linear frequency-modulated (LFM) waveforms are used to improve the tracking accuracy in the range direction [1][2][3][4][5]. Known as range-Doppler coupling, the important consideration when using LFM waveforms is the error in the range measurement in relation to the Doppler effect [5].…”

Section: Introductionmentioning

confidence: 99%

Optimal Steady-State Range Prediction Filter for Tracking with LFM Waveforms

Saho

2017

Applied Sciences

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This communication proposes a gain design method of an α-β filter with linear frequencymodulated (LFM) waveforms to achieve optimal range prediction (tracking) of maneuvering targets in steady-state. First, a steady-state root-mean-square (RMS) prediction error, called an RMS-index, is analytically derived for a constant-acceleration target. Next, a design method of the optimal gains that minimizes the derived RMS-index is proposed. Numerical analyses demonstrate the effectiveness of the proposed method, as well as producing a performance improvement over the conventional Kalman filter-based design method. Moreover, the theoretical relationship between range tracking performance and a coefficient for range-Doppler coupling of LFM waveforms is clarified. Numerical simulations using the proposed method demonstrate LFM radar tracking of maneuvering targets and prove the method's effectiveness.

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A Fast Motion Parameters Estimation Method Based on Cross-Correlation of Adjacent Echoes for Wideband LFM Radars

Cited by 3 publications

References 21 publications

A bistatic inverse synthetic aperture radar sparse aperture high‐resolution imaging algorithm with migration compensation

A bistatic inverse synthetic aperture radar sparse aperture high‐resolution imaging algorithm with migration compensation

Parameter Estimation of Fractional Bandlimited LFM Signals Based on Orthogonal Matching Pursuit

Optimal Steady-State Range Prediction Filter for Tracking with LFM Waveforms

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