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The linear frequency modulation-binary phase shift keying (LFM-BPSK) hybrid modulated signal combines the advantages of linear frequency modulation (LFM) and binary phase shift keying (BPSK). It has been extensively applied in the field of integrated radar communication. For the parameters estimation problem of LFM-BPSK signal, the traditional technologies based on the Nyquist theorem will bring a huge quantities of sample data with heavy data handling burden. This paper has presented a dual-channel cooperative sub-Nyquist sampling system for LFM-BPSK hybrid modulated signal. In the main channel, a time-interleaved sub-Nyquist sampling structure is proposed to resolve the frequency ambiguity problem caused by low sampling rate. In the other channel, a time-interleaved sub-Nyquist sampling structure based on self-mixing is proposed to estimate the phases of binary symbols and the positions of discontinuities from the low-rate samples. Simulation results have demonstrated the effectiveness and anti-noise performance of the proposed system. [ABSTRACT FROM AUTHOR]

Parameters measurement of multiple exponentially damped sinusoids (MEDS) signals is of great significance in many areas. However, recent technologies are most based on Nyquist sampling theory and thus require very high sampling rate for wide band signals. In this paper, a distributed sub-Nyquist sampling and parameters measurement method is proposed for common frequency support MEDS signals. The proposed method can measure the parameters of P common frequency support MEDS signals by P + 1 distributed sub-Nyquist sampling channels. A subspace based parameters estimation algorithm is proposed to estimate the unknown amplitudes, frequencies and damping factors of the measured MEDS signals. It can be determined that K (P + 1) + P ⌈ K / P ⌉ samples are sufficient for parameters measuring of P MEDS signals with K common frequency components, which is much smaller than previous works. Finally, we design a hardware prototype to verify the effectiveness of the proposed method. Simulation and hardware experiments have demonstrated the effectiveness and noise robustness of the proposed method. [ABSTRACT FROM AUTHOR]

In practical application, the time when the maneuvering targets enter and leave the radar coverage observation is usually unknown, which will seriously deteriorate the performance of coherent integration and target detection. To solve this problem, we propose a method based on the symmetric autocorrelation function and the proposed window Lv's transform (SAF-WLVT) for coherent integration and motion parameters estimation of maneuvering target, involving the range migration (RM) and Doppler frequency migration (DFM). Firstly, the SAF is utilized to correct the linear RM induced by target's radial velocity and range curvature caused by target's radial acceleration simultaneously. Then, the proposed WLVT is applied to eliminate the residual DFM caused by the target's radial acceleration, accumulate the target energy without introducing excess noise energy, and obtain the baseband velocity and acceleration estimations. Finally, the Doppler ambiguity number is estimated by matched filtering and 1-D parameter searching, and then the target's radial velocity is obtained. The proposed method has low computational complexity, and possesses favorable performance of target detection and parameter estimation in the high signal to noise (SNR) environment. The mathematical analysis and simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]