TY - JOUR
T1 - A Compressed Sensing-Based Coherent Integration Method with Random Agile Waveform Optimization
AU - Lang, Ping
AU - Yang, Huizhang
AU - Fu, Xiongjun
AU - Dong, Jian
AU - Yin, Junjun
AU - Yang, Jian
N1 - Publisher Copyright:
© 1965-2011 IEEE.
PY - 2026
Y1 - 2026
N2 - Frequency agile radar (FAR) exhibits robustness against active deceptive jamming and effective clutter suppression. However, effective coherent integration of target echoes under random agile waveform transmission remains challenging. This article proposes a compressed sensing (CS)-based improved sparsity adaptive matching pursuit (ISAMP) method within a joint transmit-receive processing framework. First, a Whale optimization algorithm (WOA)-based optimized random interpulse frequency and pulse repetition time joint agile (RI-FPrtJA) signal model is systematically derived. Then, the ISAMP algorithm achieves coherent integration of RI-FPrtJA echoes through two key enhancements: an adaptive regularization-based mesh mismatch correction strategy enhances mesh mismatch correction capability, and an adaptive searching extension condition reduces computational cost during sparse reconstruction. Qualitative and quantitative simulations demonstrate that ISAMP outperforms existing CS-based algorithms (e.g., orthogonal match pursuit and sparsity adaptive matching pursue) in sparse reconstruction under complex scenarios. Furthermore, the WOA-optimized RI-FPrtJA waveform can significantly improve the sparse reconstruction of agile echoes.
AB - Frequency agile radar (FAR) exhibits robustness against active deceptive jamming and effective clutter suppression. However, effective coherent integration of target echoes under random agile waveform transmission remains challenging. This article proposes a compressed sensing (CS)-based improved sparsity adaptive matching pursuit (ISAMP) method within a joint transmit-receive processing framework. First, a Whale optimization algorithm (WOA)-based optimized random interpulse frequency and pulse repetition time joint agile (RI-FPrtJA) signal model is systematically derived. Then, the ISAMP algorithm achieves coherent integration of RI-FPrtJA echoes through two key enhancements: an adaptive regularization-based mesh mismatch correction strategy enhances mesh mismatch correction capability, and an adaptive searching extension condition reduces computational cost during sparse reconstruction. Qualitative and quantitative simulations demonstrate that ISAMP outperforms existing CS-based algorithms (e.g., orthogonal match pursuit and sparsity adaptive matching pursue) in sparse reconstruction under complex scenarios. Furthermore, the WOA-optimized RI-FPrtJA waveform can significantly improve the sparse reconstruction of agile echoes.
KW - Agile waveform optimization
KW - Whale optimization algorithm (WOA)
KW - coherent integration
KW - compressed sensing (CS)
KW - improved sparsity adaptive matching pursuit (SAMP)
UR - https://www.scopus.com/pages/publications/105035652933
U2 - 10.1109/TAES.2026.3680861
DO - 10.1109/TAES.2026.3680861
M3 - Article
AN - SCOPUS:105035652933
SN - 0018-9251
VL - 62
SP - 9226
EP - 9244
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
ER -