The radon-Fourier Transform Algorithm is Predicated on the Detection of Low-Slow-Small Targets

To tackle the challenge of weak signal detection in radar systems for low, slow, and small (LSS) targets defined as low altitude, slow moving, and small sized objects, such as drones, light aircraft, or micro unmanned vehicles, this paper presents a method employing C/A code modulated spread spectrum signals to enhance the signal to noise ratio (SNR) through coherent accumulation. However, extended accumulation of full period C/A code signals induces energy spreading in the time frequency domain. To mitigate this, a two dimensional parameter estimation framework based on the Radon Fourier Transform (RFT) is proposed to achieve efficient weak signal detection for LSS targets. Simulation results demonstrate that the proposed approach reduces the required SNR by 10 dB for equivalent detection probability compared with conventional Fast Fourier Transform (FFT) based parallel search algorithms, effectively overcoming the limitations of traditional FFT methods in detecting maneuvering targets.