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This letter considers the coherent integration and detection for hypersonic target in the first‐order approximate (FOA) echo model. The proposed algorithm first accomplishes the modified pulse compression utilising the designed reference signal, then conducts the Keystone transform (KT) based coherent integration method to detect the target. Compared with the existing methods which model the received signal without considering the target's intrapulse motion, the proposed method has a lower modeling error and can maintain good noise robustness for weak hypersonic target detection. Experimental results are given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Computer vision methods have raised great interest in the manufacture of printed circuit boards (PCBs). The detection and localization of circular holes on PCBs are very important for positioning or defect detection. In this paper, a new method for such detection is presented. The proposed method first uses an adaptive edge detector to obtain the edge image. Then it utilizes the symmetry of the circle and transforms the PCB image into distance space where a Euclidean distance relationship is shown. Then a rapid circle center search (RCCS) algorithm is used to locate the center of each circle. This algorithm first scans the possible locations of each center and then filters out false selections by measuring how close the candidate center is to the contour with the Hausdorff distance. In addition, the proposed method is compared with the method based on the circular Hough transform for multiple test images in terms of speed and accuracy. [ABSTRACT FROM AUTHOR]

An iterative adaptive approach (IAA) based algorithm is presented to realise coherent integration for the random pulse repetition interval radar. The proposed method firstly removes the effect of Doppler ambiguity via phase compensation, and then accomplishes target focusing via conducting the azimuth IAA and range inverse fast Fourier transform. Theoretical analysis and numerical experiments have verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a non-iterative blind calibration algorithm for gain-phase errors is proposed. A mixing matrix is first obtained from the received observation data through blind signal separation. The mixing matrix is the product of the gain-phase error matrix and the ideal array manifold matrix. Then, a spatial spectrum is constructed by using the estimated mixed matrix. The direction corresponding to the maximum point of the spectral function is proved to be the azimuth of a certain source. Therefore, after the direction-of-arrival (DOA) is obtained by a one-dimensional spectrum search, the active calibration method can be used to estimate the gain-phase errors. The proposed algorithm is not limited to the calibration for uniform linear array (ULA), but also applicable to a non-uniform linear array. Moreover, the estimation performance of the algorithm will not be affected by the magnitude of the gain errors. Some simulations are given to verify the effectiveness and performance of the algorithm. [ABSTRACT FROM AUTHOR]