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Adaptive Bistable Stochastic Resonance Based Weak Signal Reception in Additive Laplacian Noise
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作者 Jin Liu Zan Li +1 位作者 Qiguang Miao Li Yang 《China Communications》 SCIE CSCD 2024年第1期228-241,共14页
Weak signal reception is a very important and challenging problem for communication systems especially in the presence of non-Gaussian noise,and in which case the performance of optimal linear correlated receiver degr... Weak signal reception is a very important and challenging problem for communication systems especially in the presence of non-Gaussian noise,and in which case the performance of optimal linear correlated receiver degrades dramatically.Aiming at this,a novel uncorrelated reception scheme based on adaptive bistable stochastic resonance(ABSR)for a weak signal in additive Laplacian noise is investigated.By analyzing the key issue that the quantitative cooperative resonance matching relationship between the characteristics of the noisy signal and the nonlinear bistable system,an analytical expression of the bistable system parameters is derived.On this basis,by means of bistable system parameters self-adaptive adjustment,the counterintuitive stochastic resonance(SR)phenomenon can be easily generated at which the random noise is changed into a benefit to assist signal transmission.Finally,it is demonstrated that approximately 8dB bit error ratio(BER)performance improvement for the ABSR-based uncorrelated receiver when compared with the traditional uncorrelated receiver at low signal to noise ratio(SNR)conditions varying from-30dB to-5dB. 展开更多
关键词 adaptive bistable stochastic resonance additive Laplacian noise low signal to noise ratio uncorrelated reception scheme weak signal reception
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Micro-Doppler feature extraction of micro-rotor UAV under the background of low SNR 被引量:1
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作者 HE Weikun SUN Jingbo +1 位作者 ZHANG Xinyun LIU Zhenming 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2022年第6期1127-1139,共13页
Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction ... Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required. 展开更多
关键词 micro-rotor unmanned aerial vehicle(UAV) low signal to noise ratio(SNR) MICRO-DOPPLER feature extraction parameter estimation
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