Modified implementation architecture for sinusoidal frequency modulation is introduced to extract the range information from the received radar echo. Range ambiguity problem arises because the range is calculated from...Modified implementation architecture for sinusoidal frequency modulation is introduced to extract the range information from the received radar echo. Range ambiguity problem arises because the range is calculated from the estimated phase of the received signal which is wrapped into （0, 2π]. By integrating Doppler frequency shifts, the variation of range can be estimated and used as an auxiliary information to help eliminating the corresponding range ambiguity. The performance of the new technique is evaluated by simulations. The results show that this technique is robust to sever phase noise and can be used effectively for ambiguity elimination of the modified sinusoidal frequency modulated continuous wave radar.展开更多
In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement a...In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement and the extended differentiate and cross multiply al-gorithm(DCMA)has been proposed.Firstly,the improved DFT algorithm is used to accurately obtain the distance window of human body.Secondly,phase ambiguity in phase extraction is avoided based on extended DCMA algorithm.Then,the spectrum range of refinement is determ-ined according to the peak position of the spectrum,and the respiratory and heartbeat frequency information is obtained by using chirp z-transform(CZT)algorithm to perform local spectrum re-finement.For verification,this paper has simulated the radar echo signal modulated by the simu-lated cardiopulmonary signal according to the proposed algorithm.By recovering the simulated car-diopulmonary signal,the high-precision respiratory and heartbeat frequency have been obtained.The results show that the proposed algorithm can effectively restore human breathing and heart-beat signals,and the relative error of frequency estimation is basically kept below 1.5%.展开更多
基金Sponsored by the Ministerial Level Advanced Research Foundation (323010101-50)
文摘Modified implementation architecture for sinusoidal frequency modulation is introduced to extract the range information from the received radar echo. Range ambiguity problem arises because the range is calculated from the estimated phase of the received signal which is wrapped into （0, 2π]. By integrating Doppler frequency shifts, the variation of range can be estimated and used as an auxiliary information to help eliminating the corresponding range ambiguity. The performance of the new technique is evaluated by simulations. The results show that this technique is robust to sever phase noise and can be used effectively for ambiguity elimination of the modified sinusoidal frequency modulated continuous wave radar.
文摘In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement and the extended differentiate and cross multiply al-gorithm(DCMA)has been proposed.Firstly,the improved DFT algorithm is used to accurately obtain the distance window of human body.Secondly,phase ambiguity in phase extraction is avoided based on extended DCMA algorithm.Then,the spectrum range of refinement is determ-ined according to the peak position of the spectrum,and the respiratory and heartbeat frequency information is obtained by using chirp z-transform(CZT)algorithm to perform local spectrum re-finement.For verification,this paper has simulated the radar echo signal modulated by the simu-lated cardiopulmonary signal according to the proposed algorithm.By recovering the simulated car-diopulmonary signal,the high-precision respiratory and heartbeat frequency have been obtained.The results show that the proposed algorithm can effectively restore human breathing and heart-beat signals,and the relative error of frequency estimation is basically kept below 1.5%.
