Abstract
This article presents nonlinear radar signal processing method to form an image of the Earth's surface. The method proposes to match the dynamic ranges of the received signal and of the visualization device. The essence of the method is adaptive nonlinear signal processing, which provides better local contrast of radar images and improves discrimination of individual objects. The computational complexity of the proposed algorithm is optimized and allows real-time implementation in the airborne computing systems with limited computational power. Objects with large RCS merged into large illuminated "spots"; their visibility on the surrounding background has been reduced, unwanted effects are due to the fact that the above algorithms have a single point effect. To overcome the problems, the «Retinex» algorithm is usually used. They do not take into account the local neighborhood of pixels; therefore, in cases where the image contains both highly dark and strongly light local areas, these algorithms cannot provide high-quality matching of dynamic ranges.
Highlights
The most convenient for human perception source of information about the real objects are their optical images
Reducing the time spent on matching the dynamic ranges of received signal and visualization device is an urgent problem
Two aspects of optimization can be distinguished for expression (15): the computation of the logarithm by the tabular method and the implementation of fast Gaussian blur by the infinite impulse response (IIR) filter
Summary
The most convenient for human perception source of information about the real objects are their optical images. Radar Signal Reception Unlike television and thermal imaging, radar sensors are active They independently generate and transmit electromagnetic waves towards the objects present in the observed scene and register the reflected wave to form a radar image of the targets. This is the case even if these objects are located far beyond such conglomerates and have sufficient radio contrast to detect them in comparison with the background The reason for this phenomenon is that in the process of statistical analysis, the power of the reflected signal from such objects is close to the lower limit of the range (4), or even beyond it. Due to the above reasons to distinguish them visually is very difficult
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