Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Chaotic signal reconstruction with application to noise radar system | Liu et al. EURASIP Journal on Advances in Signal Processing 2011 2011 2 http content 2011 1 2 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Chaotic signal reconstruction with application to noise radar system Lidong Liu Jinfeng Hu Zishu He Chunlin Han Huiyong Li and Jun Li Abstract Chaotic signals are potentially attractive in engineering applications most of which require an accurate estimation of the actual chaotic signal from a noisy background. In this article we present an improved symbolic dynamicsbased method ISDM for accurate estimating the initial condition of chaotic signal corrupted by noise. Then a new method called piecewise estimation method PEM for chaotic signal reconstruction based on ISDM is proposed. The reconstruction performance using PEM is much better than that using the existing initial condition estimation methods. Next PEM is applied in a noncoherent reception noise radar scheme and an improved noncoherent reception scheme is given. The simulation results show that the improved noncoherent scheme has better correlation performance and range resolution especially at low signal-to-noise ratios SNRs . Keywords Signal processing noise radar chaos parameter estimation Introduction Recently there has been a growing amount of interest in chaotic signal estimation which has been applied in the field of radar and communication 1-8 . In order to exploit chaotic signals in engineering applications there is a need of robust and efficient algorithms for reconstructing signals in the presence of noise. Initial condition estimation is an important way to reconstruct the chaotic signal because the certain chaotic signal will be obtained once the initial condition value is estimated exactly. Initial condition estimation has been investigated by many researchers and a variety of algorithms have been proposed for estimating chaotic signal 8-16 . Halving method HM 10 and extend halving .
