Enhancing Detection Performance of Multi-band Photonic Radars Through Band Fusion With Coherent Processing

In this paper, we propose and demonstrate time-frequency analysis (TFA)-based spectral gap-filling and fast Fourier transform (FFT) and particle swarm optimization (PSO)-based coherent processing methods for achieving multi-band-radar fusion in the radar receiver. For the proof-of-the-concept demonstration, we generate photonics-based S-band (2GHz-4GHz) and C-band (6GHz-8GHz) linear frequency modulated (Ph-LFM) radar transmission signals using a dual-drive-Mach-Zehnder modulator (DDMZM) and simulate them in a multi-band-radar setup to detect two objects. Using the proposed TFA-based spectral gap-filling method, the missing band signal (4GHz- 6GHz) is estimated and fused with two echos of the S-band and C-band to achieve 6GHz bandwidth. Through the FFT and PSO-based coherent processing, the phase and amplitude imbalance among the bands is corrected, leading to a 12 dB improvement in peak-to-sidelobe level power in the range-profile compared to without coherent processing. This ensures the effectiveness of the proposed band fusion methods in enhancing resolution in multi-band radar systems.