A Fast Algorithm for the Chirp Rate Estimation

2008 ◽  
Author(s):  
Jihai Cao ◽  
Ning Zhang ◽  
Lin Song
Keyword(s):  
Fast Algorithm ◽  
Chirp Rate ◽  
Rate Estimation

scholarly journals Detection of LFM Radar Signals and Chirp Rate Estimation Based on Time-Frequency Rate Distribution

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5415
Author(s):  
Ewa Swiercz ◽  
Dariusz Janczak ◽  
Krzysztof Konopko
Keyword(s):  
Parameter Estimation ◽  
Instantaneous Frequency ◽  
Estimation Methods ◽  
Joint Analysis ◽  
Cubic Phase ◽  
Chirp Rate ◽  
Time Frequency ◽  
Rate Estimation ◽  
Detection And Estimation ◽  
Frequency Rate

Linear frequency-modulated (LFM) signals are the most significant example of waveform used in low probability of intercept (LPI) radars, synthetic aperture radars and modern communication systems. Thus, interception and parameter estimation of the signals is one of the challenges in Electronic Support (ES) systems. The methods, which are widely used to accomplish this task are mainly based on transformations from time to time-frequency domain, which concentrate the energy of signals along an instantaneous frequency (IF) line. The most popular examples of such transforms are the short time Fourier transform (STFT) and Wigner-Ville distribution (WVD). However, for LFM waveforms, methods that concentrate signal energy along a line in the time-frequency rate domain may allow to obtain better detection and estimation performance. This type of transformation can be obtained using the cubic phase (CP) function (CPF). In the paper, the detection of LFM waveform and its chirp rate (CR) parameter estimation based on the extended forms of the standard CPF is proposed. The CPF was originally introduced for instantaneous frequency rate (IFR) estimation for quadratic frequency modulated (QFM) signals i.e., cubic phase signals. Summation or multiplication operations on time cross-sections of the CPF allow to formulate the extended forms of the CPF. Based on these forms, detection test statistics and the estimation procedure of LFM signal parameters have been proposed. The widely known estimation methods assure satisfying accuracy for high SNR levels, but for low SNRs the reliable estimation is a challenge. The proposed approach based on joint analysis of detection and estimation characteristics allows to increase the reliability of chirp rate estimates for low SNRs. The results of Monte-Carlo simulation investigations on LFM signal detection and chirp rate estimation evaluated by the mean squared error (MSE) obtained by the proposed methods with comparisons to the Cramer-Rao lower bound (CRLB) are presented.

Comments on discrete chirp-Fourier transform and its application to chirp rate estimation [with reply]

2002 ◽  
Vol 50 (12) ◽  
pp. 3115-3116 ◽  
Author(s):  
Xin Guo ◽  
Hong-Bo Sun ◽  
Sheng-Li Wang ◽  
Guo-Sui Liu
Keyword(s):  
Fourier Transform ◽  
Chirp Rate ◽  
Rate Estimation

scholarly journals Exploiting Chirp Rate Estimation Methods to Improve Image Formation Quality of Synthetic Aperture Radar

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
N. Rabiee ◽  
H. Azad ◽  
N. Parhizgar
Keyword(s):  
Image Formation ◽  
Estimation Methods ◽  
Complex Conjugate ◽  
Chirp Rate ◽  
Common Assumption ◽  
Rate Estimation ◽  
Estimation Algorithms ◽  
Point Target ◽  
Output Image

A common assumption in SAR image formation and processing algorithms is that the chirp rates of the transmitted and received radar signals are exactly the same. Dechirp processing is also done based on this common assumption. In real scenarios, the chirp rate of the received signal is different from that of the transmitted signal due to several reasons. In case the difference between the chirp rates of the transmitted and received signals is obvious, the demodulation and compression of the received pulse are not carried out precisely and defocusing the targets and the output images of the SAR processor results. In the present paper, a new technique is proposed to improve the image formation quality of SAR by exploiting chirp rate estimation methods. Based on the proposed technique, the chirp rate of the received signal is estimated, and then, dechirp is carried out by using a time-reversed complex conjugate filter constructed based on the estimated chirp rate. In this stage, the existing chirp rate estimation algorithms can be used. The quality of the output image is assessed using PSLR as a quantitative criterion and the average number of point target extension pixels along the azimuth direction. Simulation results indicated that the smaller the average number of point target extension pixels along with azimuth and the higher the PSLR average is, the better the output image quality would be. Therefore, output images obtained from the proposed method by exploiting chirp rate estimation algorithms would have a better quality with a higher PSLR average (14.1 and 13.6) and also the lower average number of point target extension pixels along the azimuth directions (2.1 and 4.9) than the common method with PSLR average (8.3) and an average number of point target extension pixels along the azimuth direction (7.1).

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