We present a one-bit quantified phase-based algorithm combined with the noiseless correlation transformation (PANCT) to estimate the three-dimensional (3D) parameters (i.e., azimuth angle, elevation angle, and range) of wideband near-field source via uniform circular array. We first propose a noiseless correlation transformation scheme without direction of arrival pre-estimation to obtain the correlation matrix of focusing frequency bin. Then, we exploit the phase differences to construct indefinite matrix and implement the least-square method to derive 3D parameters. Considering that the complexity scenarios include phase ambiguity and one-bit quantization, we further propose the corresponding unambiguous PANCT algorithm and one-bit quantified PANCT algorithm, respectively. Simulation results demonstrate that the proposed algorithms provide satisfactory estimation performance with low computational complexity.
Localization of a source whose half-wavelength is smaller than the array aperture would suffer from serious phase ambiguity problem, which also appears in recently proposed phase-based algorithms. In this paper, by using the centro-symmetry of fixed uniform circular array (UCA) with even number of sensors, the source’s angles and range can be decoupled and a novel ambiguity resolving approach is addressed for phase-based algorithms of source’s 3-D localization (azimuth angle, elevation angle, and range). In the proposed method, by using the cosine property of unambiguous phase differences, ambiguity searching and actual-value matching are first employed to obtain actual phase differences and corresponding source’s angles. Then, the unambiguous angles are utilized to estimate the source’s range based on a one dimension multiple signal classification (1-D MUSIC) estimator. Finally, simulation experiments investigate the influence of step size in search and SNR on performance of ambiguity resolution and demonstrate the satisfactory estimation performance of the proposed method.
Random Pulse Repetition Interval Compressed Sensing Radar (RPRICSR) has superiorities on target detection, unambiguous velocity measurement as well as anti-velocity jamming for its signal randomness. However, RPRICSR cannot detect the micro motion targets effectively under the presence of micro motion false targets within present echo processing methods. This paper firstly combined Short Sparse Recovery (SSR) method with RPRI signal under the frame of Compressed Sensing. Then the fact that echo signals of true and false micro motion targets are sparse in different dictionaries are utilized to separate the true and false micro motion targets based on a union dictionary. The proposed method is proved to be effective compared to the traditional signal processing methods of RPRICSR according to the simulation results.
Intra-pulse frequency coded (IPFC) signal, with its large time-bandwidth and low probability of interception characteristics, is widely applied to anti-jamming radar system. This paper focuses on the efficiency of interrupted sampling repeater jamming (ISRJ) under IPFC signal, and the influence on jamming effect with different signal forms and waveform parameters is mainly analyzed. The simulation results show that the ISRJ of step frequency coded signal and liner modulated frequency signal have similar jamming performance. The ISRJ of random frequency coded signal can only form a single false target at direct forwarding mode. Furthermore, with the increasing of the sub-pulse number, the ISRJ performance of random frequency coded signal will be reduced.
In order to resolve the phase ambiguity in parameter estimation of a high frequency source with uniform circular array (UCA), this paper presents an algorithm via clustering to obtain the source’s 3-D parameters (azimuth angle, elevation angle, and range) unambiguously. By computing the phase differences between centro-symmetric sensors and employing some mathematics, angle parameters of the source can be decoupled and be estimated. Then, a plural matrix is developed based on ambiguity search, where each column includes a plural constituted by real angle parameters. Further, the unambiguous angle parameters can be obtained by the means of clustering based on range. A one dimension MUSIC method is applied to estimate range parameter after the angle parameters have been obtained. Numerical examples are also presented to demonstrate the performance of the proposed algorithm.
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