Spreading Waveform Estimation of Long-Code DS-SS Signals Based on Missing-Data Model
Ping Wei · Dianzi xuebao · 2010
In the context of signal interception applications,a novel model based on missing-data model is proposed to the blind synchronization and the estimation of the spreading waveform for the long code Direct Sequence Spreading Spectrum(DS-SS) signals.In the blind synchronization step,the Frobenius norm maximization algorithm,a classic blind synchronization method used in short code DS-SS signals,is extended to our missing-data model and its asymptotic efficiency is verified; in the step of spreading waveform estimation,an alternative projection(AP) algorithm with low computational complexity used to weighted low-rank approximation(WLRA) is proposed.Based on the missing-data model,the proposed method can directly exploit the received data.Therefore,significant performance improvement is observed in simulations,especially under the scenarios with short data length,than other existing approaches,which only exploit the auto-correlation matrix of the received data and lead to obvious performance loss.