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Using the sparse property of the signal from a marine target with quadratic modulated frequency (QFM) micromotion signature, the detection in sparse domain is studied. An algorithm for separation of sea clutter and micro-Doppler signal is proposed based on the Morphological Component Analysis (MCA). At first, the signal model of a marine target with micromotion is established, which can be modelled...
The micro-Doppler (m-D) signature of a sea surface target is employed for detection and modeled as a quadratic frequency modulated (QFM) signal. Furthermore, a novel long-time coherent integration method, i.e., Radon-fractional ambiguity function (RFRAF), is proposed to detect the m-D signal, which can compensate the range and Doppler migrations simultaneously. The m-D signal can be well matched and...
In this letter, a novel long-time coherent integration method, known as the Radon-linear canonical transform (RLCT), is proposed for detection of a low observable moving target in sea clutter. The micro-Doppler (m-D) of a sea-surface target is studied and modeled as multiple linear-frequency-modulated signals, which result from the accelerated and 3-D rotated movements. The RLCT-based algorithm employs...
The sparse decomposition principle is introduced and a detection algorithm of target with micro-motion embedded in sea clutter is proposed, which can detect and extract micro-Doppler (m-D) signals in low signal-to-clutter ratio environment. Firstly, the three dimensional model of radar echo from micro-motion target is established including the 3-D rotated movements (pitch, roll, and yaw movements)...
Aimed at the target detection problems of strong echoes in SAR images under complex background, an adaptive target detection algorithm is proposed on the basis of the multi-scale auto-convolution variance saliency (MSAVS). First, with the calculation of MSAVS, the variance saliency map is obtained by using the presented algorithm. Second, an auto-selecting-threshold detector is constructed according...
This paper introduces fractal-based variable step-size least mean square(FB-VSLMS) algorithm and proposes a model for radar target detection in sea clutter. FB-VSLMS algorithm deals with a specific class of fractal signals and except one parameter requiring time-varying constraints, the constraints on the remaining parameters are time-invariant. And the step-size matrix is determined completely with...
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