This paper considers the complex-valued mixing matrix estimation and direction-of-arrival (DOA) estimation of synchronous orthogonal frequency hopping (FH) signals in the underdetermined blind source separation (UBSS). A novel mixing matrix estimation algorithm is proposed by detecting single source points (SSPs) where only one source contributes its power. Firstly, the proposed algorithm distinguishes the SSPs by the comparison of the normalized coefficients of time frequency (TF) points, which is more effective than existing detection algorithms. Then, mixing matrix of FH signals can be estimated by the hierarchical clustering method. To sort synchronous orthogonal FH signals, a modified subspace projection method is presented to obtain the DOAs of FH. One superiority of this paper is that the estimation accuracy of the mixing matrix can be significantly improved by the proposed SSPs detection criteria. Another superiority of this paper is that synchronous orthogonal FH signals can be sorted in underdetermined condition. The experimental results demonstrate the efficiency of the two proposed algorithms.

This paper proposes a novel estimation method, named double scale two dimensional frequency distribution (DSTFD), to estimate the parameters of quadratic frequency modulated (QFM) signals. In the DSTFD, by using a novel parametric instantaneous self-correlation function and the idea of the keystone transform, the QFM signals are transformed into two-dimensional frequency domain, and the QFM signals are detected by searching peaks. To reduce computational cost, a double scale (DS) estimation strategy, which consists of coarse estimation and fine estimation, is proposed. The DS estimation strategy can be implemented by using the Chirp Z-transform and an improved transform named local scaled Fourier transform (LSFT). The LSFT only consists of complex multiplications, fast Fourier transform (FFT), and inverse FFT operations. The implementation, anti-noise performance, and computational cost are analyzed for the proposed method. Through simulations and analyses, the results demonstrate that the DSTFD outperforms other compared algorithms. INDEX TERMS Double scale two dimensional frequency distribution (DSTFD), quadratic frequency modulated (QFM), parameter estimation, parametric instantaneous self-correlation function (PISCF), double scale estimation strategy.

In an inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, the azimuth echo signals of the target are always modeled as multicomponent quadratic frequency modulation (QFM) signals. The chirp rate (CR) and quadratic chirp rate (QCR) estimation of QFM signals is very important to solve the ISAR image defocus problem. For multicomponent QFM (multi-QFM) signals, the conventional QR and QCR estimation algorithms suffer from the cross-term and poor anti-noise ability. This paper proposes a novel estimation algorithm called a two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD) for QFM signals parameter estimation. The 2D-PMPCRD employs a multi-scale parametric symmetric self-correlation function and modified nonuniform fast Fourier transform-Fast Fourier transform to transform the signals into the chirp rate-quadratic chirp rate (CR-QCR) domains. It can greatly suppress the cross-terms while strengthening the auto-terms by multiplying different CR-QCR domains with different scale factors. Compared with high order ambiguity function-integrated cubic phase function and modified Lv’s distribution, the simulation results verify that the 2D-PMPCRD acquires higher anti-noise performance and obtains better cross-terms suppression performance for multi-QFM signals with reasonable computation cost.

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