TY - GEN
T1 - Parameter Optimization of Sparse Fourier Transform for Radar Target Detection
AU - Zhang, Hongchi
AU - Shan, Tao
AU - Liu, Shengheng
AU - Tao, Ran
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/21
Y1 - 2020/9/21
N2 - The sparse Fourier transform (SFT) can dramatically accelerate the spectral analyses by leveraging the inherit sparsity in radar echoes. However, a satisfactory accuracy-complexity trade-off commonly requires sophisticated empirical parameter tuning. In this context, this work attempts to enhance SFT by optimizing the parameter selection mechanism. We first derive closed-form expressions of two performance metrics with respect to the detection and false-alarm rates. On top of this, a parameter optimization algorithm is designed. The proposed scheme is able to automatically arrive at a optimized parameter settings considering the a priori knowledge and the performance requirements, which is confirmed by numerical simulations.
AB - The sparse Fourier transform (SFT) can dramatically accelerate the spectral analyses by leveraging the inherit sparsity in radar echoes. However, a satisfactory accuracy-complexity trade-off commonly requires sophisticated empirical parameter tuning. In this context, this work attempts to enhance SFT by optimizing the parameter selection mechanism. We first derive closed-form expressions of two performance metrics with respect to the detection and false-alarm rates. On top of this, a parameter optimization algorithm is designed. The proposed scheme is able to automatically arrive at a optimized parameter settings considering the a priori knowledge and the performance requirements, which is confirmed by numerical simulations.
KW - Neyman-Pearson detection
KW - Time-frequency analysis
KW - discrete Fourier transform
KW - numerical algorithms
KW - parameter optimization
UR - https://www.scopus.com/pages/publications/85091795513
U2 - 10.1109/RadarConf2043947.2020.9266417
DO - 10.1109/RadarConf2043947.2020.9266417
M3 - Conference contribution
AN - SCOPUS:85091795513
T3 - IEEE National Radar Conference - Proceedings
BT - 2020 IEEE Radar Conference, RadarConf 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Radar Conference, RadarConf 2020
Y2 - 21 September 2020 through 25 September 2020
ER -