Burst signal detection and estimation in low SNR and high-dynamic environments

Aiming to the burst signal detection in high-dynamic environments, an NLFM signal parameter estimation algorithm based on high order items eliminated sequentially was presented, which converting the problem into a relatively simple issue, that is LFM signal parameter estimation. The proposed scheme has the feature of concise principle and low computational complexity, and was easily used for projects. Besides, a burst communication signals detection algorithm named as adaptive FFT PAPR (peak to average ratio) threshold detecting was raised, which could work well even the received signal power varying severely. Simulation results show that both of the two schemes could achieve signal detection and parameter estimation accurately in high-dynamic circumstances while the SNR (signal to noise ratio) is only -27 dB.