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The successful design of an orthogonal waveform set is crucial for orthogonal netted radar systems and MIMO radar systems. An orthogonal waveform set design method of time-stagger coding and hyperbolic coding stepped-frequency linear frequency modulated (SFLFM) pulse train is proposed in this paper. First, the transmitting time of SFLFM subpulses is time-stagger coded to decrease the autocorrelation sidelobe peaks (ASP) and cross-correlation peaks (CCP) when | τ | ≥ T p , where τ is the time delay and T p is the subpulse duration. Then the frequency firing order of the SFLFM subpulses for every waveform is hyperbolic coded to lower the CCP when | τ | < T p . When the subpulse number of SFLFM pulse train is N , the ASP and CCP of the designed orthogonal waveform set is approximately 1 / N . The design procedure of the proposed method is demonstrated via a case study, and the orthogonality of the designed waveform set is verified by simulating the autocorrelation function, cross-correlation function, auto-ambiguity function and cross-ambiguity function. [ABSTRACT FROM AUTHOR]

Abstract: In order to improve the detection performance of constant false alarm rate (CFAR) detectors in multiple targets situations, a CFAR detector based on the maximal reference cell (MRC) named MRC-CFAR is proposed. In MRC-CFAR, a comparison threshold is generated by multiplying the amplitude of MRC by a scaling factor. The number of the reference cells left, whose amplitudes are smaller than the comparison threshold, is counted and compared with a threshold integer. Based on the comparison result, proper reference cells are selected for detection threshold computation. A closed-form analysis for MRC-CFAR in both homogeneous and non-homogeneous environments is presented. The performance of MRC-CFAR is evaluated and compared with other CFAR detectors. MRC-CFAR exhibits a very low CFAR loss in a homogeneous environment and performs robustly during clutter power transitions. In multiple targets situations, MRC-CFAR achieves a much better detection performance than switching CFAR (S-CFAR) and order-statistic CFAR (OS-CFAR). Experiment results from an X-band linear frequency modulated continuous wave radar system are given to demonstrate the efficiency of MRC-CFAR. Because ranking reference cells is not required for MRC-CFAR, the computation load of MRC-CFAR is low; it is easy to implement the detector in radar system in practice. [Copyright &y& Elsevier]

The sparsity characteristic, which is the foundation of the compressive sensing (CS) theory, has been widely used in the inverse synthetic aperture radar (ISAR) imaging field. However, the performance of the traditional CS-based sparse aperture ISAR imaging method is limited in low signal to noise ratio (SNR) and/or sampling rate (SPR). Inspired by the low-rank property of the final ISAR image, a new sparse aperture ISAR imaging model by jointly using the sparse characteristic and low-rank property is proposed in this paper. Considering the effective solution of the proposed reconstruction model, the optimization problem is decomposed into several sub-problems under the framework of linearized alternating direction method with adaptive penalty (LADMAP) approach. Furthermore, in order to improve the computing efficiency of the proposed algorithm, a fast singular value decomposition (SVD) free algorithm is finally proposed. Both simulated and measured data experiments verify the effectiveness of the proposed algorithms, especially under the condition of low SNR and/or SPR. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present two joint timing recovery and decoding algorithms for non-binary low-density parity-check (LDPC) coded systems. To estimate the timing offset, the first algorithm utilizes the percentage of the satisfied check nodes (SCNs), while the second algorithm utilizes the soft decision metrics (SDMs). Both SCNs and SDMs are fed back from the LDPC decoder, which can be implemented by either the well-known q-ary sum-product algorithm (QSPA) or other low complexity algorithms, such as the X-EMS algorithms. Simulation results show that the proposed algorithms suffer from a little performance degradation compared with the perfect timing system. Simulation results also show that X-EMS algorithms aided by the timing recovery algorithm using SDMs outperform QSPA aided by the timing recovery algorithm using SCNs, but with a much lower complexity. This implies that the performance is mainly affected by the timing recovery algorithms. [Copyright &y& Elsevier]