TY - JOUR
T1 - Parameters estimation algorithm of LFM pulse compression radar signal
AU - Wen, Jing Yang
AU - Zhang, Huan Yu
AU - Wang, Yue
PY - 2012/7
Y1 - 2012/7
N2 - Under low signal noise ratio, estimation accuracy using classical algorithms, such as envelope-demodulation and instant autocorrelation spectrum, can't satisfy with the system requirements. To enhance the estimating accuracy of pulse repetition interval, pulse width and frequency modulation rate, an integrated method of multi-parameter estimation is proposed based on fractional Fourier transform (FRFT) in this paper. The focusing capability of FRFT was used for linear frequency modulation (LFM) signal and the relativity of estimation algorithm for each parameter was considered. Moreover, the founded test platform was utilized that transmits and receives LFM pulse compression radar signal to do a trial on algorithm. The results demonstrate its feasibility. The proposed method could not only get high estimation accuracy but also have good ability in real-time processing.
AB - Under low signal noise ratio, estimation accuracy using classical algorithms, such as envelope-demodulation and instant autocorrelation spectrum, can't satisfy with the system requirements. To enhance the estimating accuracy of pulse repetition interval, pulse width and frequency modulation rate, an integrated method of multi-parameter estimation is proposed based on fractional Fourier transform (FRFT) in this paper. The focusing capability of FRFT was used for linear frequency modulation (LFM) signal and the relativity of estimation algorithm for each parameter was considered. Moreover, the founded test platform was utilized that transmits and receives LFM pulse compression radar signal to do a trial on algorithm. The results demonstrate its feasibility. The proposed method could not only get high estimation accuracy but also have good ability in real-time processing.
KW - Fractional Fourier transform
KW - Linear frequency modulation signal
KW - Parameter estimation
KW - Pulse compression radar
KW - Radar
UR - https://www.scopus.com/pages/publications/84867420528
M3 - Article
AN - SCOPUS:84867420528
SN - 1001-0645
VL - 32
SP - 746
EP - 750
JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
IS - 7
ER -