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Detection Methods of Manoeuvring Targets in Narrowband and Wideband Radars

Author: XuShuWen
Tutor: ShuiPengLang
School: Xi'an University of Electronic Science and Technology
Course: Signal and Information Processing
Keywords: Narrowband Radar Wideband radar Maneuvering Target Distance extended targets Phase history Fractional Fourier Transform Median filter Gaussian white noise Modified correlation matrix CFAR Nonlinear contraction mapping Geometric mean accumulation Waveform cross-entropy Sparsity
CLC: TN957.51
Type: PhD thesis
Year: 2011
Downloads: 284
Quote: 1
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Narrowband, wideband radar system under the maneuvering target detection radar detection field has always been a difficult problem, the field of radar technology has become a hot research topic. Narrow-band radar system, the radar range resolution cell is very long. Therefore, the goal is not coherent processing time walking across from the unit. For a long time coherent processing of radar clutter noise or weak target detection is meaningful, but prolonged observation target maneuver inevitably occur. Maneuvering target so that the target radar echo phase history becomes very complicated in this case the traditional Fourier analysis can not be well effective accumulation target echo. In this thesis work, the fractional Fourier transform is used to effectively accumulate phase history is more complex target echo, and obtain better detection performance. In wideband radar system, the radar has a high range resolution. Therefore, the narrow circumstances \Wideband radar system, the target is resolved into multiple scattering units. Therefore, the target detection distance is called extended target detection. Target makes maneuvering targets in different inter-echo pulse will inevitably move across the distance unit, and because of the rotation of the target and the target scatterers restructuring, so that the target cells at different distances on the echo phase become disorganized, very difficult modeling. Because of the lack of echo model, the paper on broadband maneuvering target detection research mainly focused on multi-pulse from the image feature detection, we propose a series of practical and effective broadband expansion target detector distance. Contents of this thesis can be summarized as the following five parts: the first part, we briefly introduce narrow maneuvering target detection problems currently facing, reviews current some of the ways to solve the problem. Then, based on the current problems of detection methods, we based on fractional Fourier transform, image domain denoising and double feature detector presents a strong noise background in the non-parametric weak target detection method. This method will be signaled by a series of two-dimensional fractional Fourier transform gray scale image representation, and use multiple hard threshold filter and median filter in filtering noise while preserving the signal characteristics, and finally, after extraction of the amplitude noise filter on the image Strong pixel size and amplitude characteristics of these two peaks were detected, and then put forward based on two characteristics of non-parametric object detection scheme. For a variety of typical narrowband maneuvering target echo signal Experimental results show that the proposed detection scheme is effective when compared with conventional detection scheme has better detection performance, and has better robustness. The second part, we present a Gaussian white noise background detection distance extended targets a feature detection method. Detection scheme presented in this chapter is about the expansion of the target from the generic detection framework. This detection method using two successive mixer output Wigner-Ville distribution (WVD) geometric characteristics. In this test method, each time-frequency distribution operation is used to highlight the time-frequency characteristics of the target echo. Two simple image processing tools (threshold operation and morphological filtering) is used to extract the corresponding time-frequency structure of the target. This method is applicable to the case of the target range walk occurs, and the density of the target, such as scattering, target type, and the energy level of Gaussian noise prior information no special requirements. Due to a combination of energy information and target echo time-frequency structure information specific proposed method to obtain a good detection performance. The third part, we propose a Gaussian white noise background in the use of multi-pulse distance as the amendment extended target detection distance cross-correlation matrix (MCOM) detector. It is used for noise suppression by the sigmoid-type contraction mapping and refining distance like the cross-correlation accumulation components. HRRP based on the target cells are sparse strong scattering the fact that we designed to refine the nonlinear contraction mapping HRRP received. With this mapping, the receiving distance like most of the noise points to be removed, and the target characteristics associated with strong scattering unit is preserved. Because in addition to walking distance to target beyond the scattering geometry remained almost unchanged, so successive pulses obtained from refining target distance like a highly similar, while the noise of randomness makes the noise from such refined dissimilar. Refined from multi-pulse correlation matrix as the correction is used to measure the similarity of them. We construct fix all the elements of correlation matrix as a weighted accumulation test statistic thus be detected. Proposed detector does not rely on strict target echo model and can be applied in the case of relatively wide. Measured data and simulated noise data were used to evaluate proposed expansion target detector distance. Experimental results show that: Compared with the existing detection methods, the method to obtain a better target detection performance. The fourth part, we propose a new Gaussian white noise in the background from the expansion of maneuvering target detector. It consists of a two-dimensional nonlinear noise suppression for contraction mapping and geometric mean accumulation components. Obtained from multiple pulses constitute a two-dimensional image through a sort distance pulse images. Based on local statistical characteristics of the image, we have designed a family of two-dimensional nonlinear contraction mapping effective to suppress noise and keep the echo signal. Filtered multi-pulse refined as the geometric mean of the distance accumulated constitute the detector's test statistic. The test statistic reflects the target distance as the relevance of the waveform and the noise from the refining of non-zero scattering elements as the sparsity and location of randomness. Theoretical analysis and experiments based on measured data show that the detector white noise background air maneuvers in the distance extended target detection is very effective. The fifth part, we propose a cross-entropy-based waveform (waveform cross entropy, WCEN) detector in a homogeneous meteorological clutter detection speed flight maneuvering targets. The detector input by the observation window to get a series of coherent pulses constitute the complex HRRP. Observation window contains a detector of the detection window and the window surrounds reference distance unit, and the reference distance in the received data unit contains only clutter data constitute secondary data. The detector includes a pulse along the approximate dimensions whitening filter, and a slow time at a distance in WCEN detector wiki. The former received data in each dimension from the operation unit, thereby enhancing the clutter and target echo whitened. Then, each pair of filtered HRRP WCEN excavated target HRRP three inherent characteristics: sparsity, similarity and energy characteristics. Each pair HRRP WCEN average was used as test statistic to judgment target exists. Based on obtained from a high resolution radar target data measured and simulated weather clutter data, we complete assessment based WCEN detector. Experimental results show that the target speed in the case of maneuver, compared to other existing detector, detector based WCEN get better detection performance.

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