LFM Signal Analysis Based on Improved Lv Distribution

In this paper, we propose a parameter estimation method named improved Lv distribution (ImLVD) for linear frequency modulated (LFM) signals. In this method, based on the scaling principle, we present a two-scale estimation strategy to acquire low computational cost. The two-scale estimation strategy includes coarse estimation operation and fine estimation operation. To implement the strategy, improved scaled Fourier transform (ISFT) and Chirp-Z transform (CZT) operation are used, where the ISFT can be implemented by fast Fourier transform (FFT) and complex multiplications. By changing the frequency searching range of ISFT, the ISFT is used in different frequency ranges. To improve the anti-noise, we present an improved parameter selection criterion which can reduce the noise correlation effectively. In this paper, the implementation, anti-noise performance, and computational cost are analyzed. Through simulations and analyses, we demonstrate that the ImLVD outperforms the compared algorithms.

[1]  L. Rabiner,et al.  The chirp z-transform algorithm , 1969 .

[2]  T. Claasen,et al.  THE WIGNER DISTRIBUTION - A TOOL FOR TIME-FREQUENCY SIGNAL ANALYSIS , 1980 .

[3]  M. Portnoff Time-frequency representation of digital signals and systems based on short-time Fourier analysis , 1980 .

[4]  F. Hlawatsch,et al.  Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.

[5]  Luís B. Almeida,et al.  The fractional Fourier transform and time-frequency representations , 1994, IEEE Trans. Signal Process..

[6]  John C. Wood,et al.  Radon transformation of time-frequency distributions for analysis of multicomponent signals , 1994, IEEE Trans. Signal Process..

[7]  Sergio Barbarossa,et al.  Analysis of multicomponent LFM signals by a combined Wigner-Hough transform , 1995, IEEE Trans. Signal Process..

[8]  Vladimir Katkovnik A new form of the Fourier transform for time-varying frequency estimation , 1995, Signal Process..

[9]  Andrew K. Chan,et al.  Linear frequency-modulated signal detection using Radon-ambiguity transform , 1998, IEEE Trans. Signal Process..

[10]  Guoan Bi,et al.  Adaptive Harmonic Fractional Fourier Transform , 1999, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).

[11]  P. Willett,et al.  Hough transform for long chirp detection , 2002 .

[12]  P. O'Shea A new technique for instantaneous frequency rate estimation , 2002, IEEE Signal Processing Letters.

[13]  Jianyu Yang,et al.  Multicomponent chirp signals analysis using product cubic phase function , 2006, Digit. Signal Process..

[14]  Daming Shi,et al.  Maximum Amplitude Method for Estimating Compact Fractional Fourier Domain , 2010, IEEE Signal Processing Letters.

[15]  Mengdao Xing,et al.  ISAR Imaging of Maneuvering Targets Based on the Range Centroid Doppler Technique , 2010, IEEE Transactions on Image Processing.

[16]  Igor Djurovic,et al.  Performance of Instantaneous Frequency Rate Estimation Using High-Order Phase Function , 2010, IEEE Transactions on Signal Processing.

[17]  I. Djurovic,et al.  Integrated Cubic Phase Function for Linear FM Signal Analysis , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[18]  Guoan Bi,et al.  LFM signal detection using LPP-Hough transform , 2011, Signal Process..

[19]  Mengdao Xing,et al.  Lv's Distribution: Principle, Implementation, Properties, and Performance , 2011, IEEE Transactions on Signal Processing.

[20]  Guoan Bi,et al.  Performance analysis on Lv distribution and its applications , 2013, Digit. Signal Process..

[21]  Qing Huo Liu,et al.  ISAR Imaging of Targets With Complex Motion Based on the Chirp Rate–Quadratic Chirp Rate Distribution , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Thierry Chonavel,et al.  Analysis of multicomponent LFM signals by Teager Huang-Hough transform , 2014, IEEE Transactions on Aerospace and Electronic Systems.

[23]  Zhi-Chao Zhang Unified Wigner-Ville distribution and ambiguity function in the linear canonical transform domain , 2015, Signal Process..

[24]  Tao Su,et al.  ISAR Imaging of Targets With Complex Motions Based on Modified Lv’s Distribution for Cubic Phase Signal , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[25]  J. Xie,et al.  Coherently integrated cubic phase function for multiple LFM signals analysis , 2015 .

[26]  Shuang Wu,et al.  Parameter estimation for maneuvering targets with complex motion via scaled double-autocorrelation transform , 2016, Digit. Signal Process..

[27]  Tülay Yildirim,et al.  FMCW Signal Detection and Parameter Extraction by Cross Wigner–Hough Transform , 2017, IEEE Transactions on Aerospace and Electronic Systems.

[28]  Guoan Bi,et al.  Sparsity-Driven SAR Imaging for Highly Maneuvering Ground Target by the Combination of Time-Frequency Analysis and Parametric Bayesian Learning , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[29]  Xiaodong Xiong,et al.  Angle estimation for bistatic MIMO radar in the presence of spatial colored noise , 2017, Signal Process..

[30]  Qing Huo Liu,et al.  Parameterized Centroid Frequency-Chirp Rate Distribution for LFM Signal Analysis and Mechanisms of Constant Delay Introduction , 2017, IEEE Transactions on Signal Processing.

[31]  Xiaodong Xiong,et al.  Angle and mutual coupling estimation in bistatic MIMO radar based on PARAFAC decomposition , 2017, Digit. Signal Process..

[32]  Guisheng Liao,et al.  Performances Analysis of Coherently Integrated CPF for LFM Signal Under Low SNR and Its Application to Ground Moving Target Imaging , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[33]  Feng Xia,et al.  Joint Range-Doppler-Angle Estimation for Intelligent Tracking of Moving Aerial Targets , 2018, IEEE Internet of Things Journal.

[34]  Guan Gui,et al.  Deep Learning for Super-Resolution Channel Estimation and DOA Estimation Based Massive MIMO System , 2018, IEEE Transactions on Vehicular Technology.

[35]  Xinyu Zhang,et al.  Direction finding in bistatic MIMO radar with unknown spatially colored noise , 2018, 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP).

[36]  Hong Gu,et al.  Fast method for radar maneuvering target detection and motion parameter estimation , 2018, Multidimens. Syst. Signal Process..

[37]  Ke Wang,et al.  Angle estimation and mutual coupling self-calibration for ULA-based bistatic MIMO radar , 2018, Signal Process..

[38]  Liren Zhang,et al.  A Novel Approach of Slope Detection Combined with Lv's Distribution for Airborne SAR Imagery of Fast Moving Targets , 2018, Remote. Sens..

[39]  Fangqing Wen,et al.  Direction finding in MIMO radar with large antenna arrays and nonorthogonal waveforms , 2019, Digit. Signal Process..

[40]  Yu Wang,et al.  QFM Signals Parameters Estimation Based on Double Scale Two Dimensional Frequency Distribution , 2019, IEEE Access.

[41]  Gong Zhang,et al.  Joint DOD and DOA Estimation for Bistatic MIMO Radar: A Covariance Trilinear Decomposition Perspective , 2019, IEEE Access.

[42]  Xianpeng Wang,et al.  Polarization Channel Estimation for Circular and Non-Circular Signals in Massive MIMO Systems , 2019, IEEE Journal of Selected Topics in Signal Processing.

[43]  Xianpeng Wang,et al.  Assistant Vehicle Localization Based on Three Collaborative Base Stations via SBL-Based Robust DOA Estimation , 2019, IEEE Internet of Things Journal.

[44]  Jie Yang,et al.  Data-Driven Deep Learning for Automatic Modulation Recognition in Cognitive Radios , 2019, IEEE Transactions on Vehicular Technology.