One of the most important ways to improve the radar systems based on smart antennas is improved accuracy angle measurements and increasing of angular resolution. In this regard, the current problem is to restore the image of the object with superresolution. This inverse problem is reduced to a Fredholm integral equation (1), where U() is the signal received by the scanning; – angular region of location of the signal source; I(, ) – desired angular distribution of the reflected signal amplitude, F(, ) – radiation pattern. The set problem based on the intelligent analysis and digital signal U() is to restore the source's image with superresolution.
In contrast to conventional phased array, the signals received by each transmitter of smart antennas can be recorded digitally. The new signal processing method is based on extrapolation of signals received by each element of smart antennas, beyond the aperture. This method provides a synthesized smart antennas with significantly more emitters and with increased aperture by the same factor. As a result, both accuracy of angular measurements and angular resolution increase.
The best results were obtained using the extrapolation with the Berg linear prediction method. The algorithm predicts the values of signals for the aperture array which are ten times greater than the original, with negligible error. Numerical studies have shown that the Rayleigh criterion exceed 6–7 times in this problem.
An important characteristic of solutions is a minimum signal/noise ratio, which yet allows superresolution image reconstruction. Stability of the solutions and quality of image reconstruction were examined on the mathematical model. The results of numerical studies have shown that the angular resolution is 4–10 times increased under the signal/noise ratio 12–13 dB, i.e. which is much less than by the known methods.
The proposed new method of signal processing, based on digital aperture synthesis, will significantly improve accuracy of angle measurement. It provides a stable restoration of detailed images of the objects with superresolution in the presence of small distortions. The algorithm of the method can be implemented in real time mode.
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