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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]

Interrupted sampling repeater jamming (ISRJ) is an active coherent jamming with the characteristic of suppression and deception, which poses a great threat to modern radars. In this work, a false target identification and suppression method based on random interpulse frequency coding linear frequency modulation (RIFC-LFM) signal processing is proposed. First, we analyze the characteristics of the RIFC-LFM signal and ISRJ using the ambiguity function and cross ambiguity function, respectively. Next, taking advantage of the property that most of the false targets formed by ISRJ will be whitened after range-Doppler processing, a false target range-Doppler (RD) spectrum reconstruction method is proposed. Using the reconstructed false target RD spectrum, we can obtain the positions of the unwhitened false targets in the RD spectrum and distinguish the true and false targets. Finally, we design the suppression matrix based on the reconstructed false target RD spectrum to suppress the false targets. The simulation results demonstrate that the proposed approach can effectively suppress three different ISRJs without estimating the ISRJ parameters. • An RIFC-LFM signal is proposed, which has a "thumbtack" ambiguity function. • An ISRJ identification and suppression method is proposed. • The proposed method is applicable for suppressing three different ISRJs. • The proposed method does not need to estimate ISRJ parameters. [ABSTRACT FROM AUTHOR]

In this paper, a two-dimensional (2D) direction of arrival (DOA) estimation algorithm by a large-space T-shaped array is proposed. The used T-shaped array consists of a generalized unfolded co-prime array and a symmetrically unfolded co-prime array. The minimum element space (MES) of the proposed T-shaped array can exceed half-wavelength of received signals. The symmetry of the T-shaped array is used to construct an extended cross-covariance matrix, singular value decomposition (SVD) of which can obtain multiple signal subspaces. By combining the co-prime characteristic of element spacing with the rotational invariance of uniform linear array, three extended signal subspaces can be obtained without using virtual elements. Using the three extended signal subspaces, high-precision 2D DOA estimation can be got. The proposed T-shaped array has strong robustness to mutual coupling. The proposed method can eliminate angle ambiguity caused by large-space and has higher estimation precision than many similar 2D DOA estimation algorithms. Many simulation results can prove the performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, a high-precision two-dimensional (2D) direction of arrival (DOA) estimation algorithm by three parallel uniform linear arrays (ULAs) is proposed. Both the internal spacing of each sub-array and the spacing between two adjacent sub-arrays can exceed the half-wavelength of incident signal. An extended propagator method (PM) algorithm is introduced to obtain a multiple extended propagator matrix by processing the covariance matrix of received signals. Then, by using the extended propagator matrix, unambiguous and high-precision 2D DOA estimation can be obtained without extra pairing process. For the proposed array construction, mutual coupling effect can be ignored as long as the element interval is large enough. The extended PM algorithm based on the proposed array has far higher precision than the existing similar algorithms, which can be proved by some simulation experiments. [ABSTRACT FROM AUTHOR]

The time-frequency analysis of nonstationary multicomponent linear frequency modulation (LFM) signals is still a challenging task due to their cross-term interferences. In this paper, a novel signal-dependent adaptive compact kernel based time-frequency distribution (CKD) named regional adaptive CKD (RACKD) is proposed. The proposed RACKD firstly represents the signal in the Doppler-lag (ν , τ) ambiguity domain, and then applies a signal-dependent regional compact kernel to filter the cross-term interferences, with preserving the auto-terms in the ambiguity domain. By automatically selecting the auto-terms' distribution area which represents the signals in the ambiguity domain, the parameters of the newly designed signal-dependent regional compact kernel can be adaptively set according to the signals to be processed. The proposed RACKD shows a more stable performance in the ability of cross-term rejection and component energy of signals concentration around their respective instantaneous frequency, compared to several existing state-of-the-art methods. Both simulation results and experimental results based on sea-truth data have validated the improved performance of the proposed method. For the simulated signal composed of one weak and two strong LFM components with crossing frequency, the proposed RACKD shows up to 2.6% gain as compared to the signal-dependent multidirectional distribution (MDD) approach. [ABSTRACT FROM AUTHOR]