Spatiotemporal processing of broadband signals based on the linear prediction model

The main developments in the field of radar surveillance systems are aimed at studying their functioning, taking into account the influence of various factors, such as the effect of interference. The most important thing seems to be the detection of a broadband signal, which makes it possible to increase the range and speed resolution. This raises the problem of suppressing broadband interference with existing methods. The paper develops methods for processing broadband signals in the presence of active interference as applied to the use in systems with various variants of spatio-temporal antenna elements, in particular on the example of linear antenna arrays. The approach is based on the representation of signals and interference recorded by a digital antenna array in the form of multidimensional spatiotemporal processes, i.e. functions of spatial and temporal coordinates. This is due to both the spatial distribution of the antenna array elements and the spatial distribution of interference. Bayesian signal detector is the optimal algorithm and has the best characteristics, but at the same time its practical implementation is extremely difficult, carried out in the field of spatiotemporal coordinates. The investigated processing algorithms are based on the linear prediction model, i.e. by using the model of a Markov random process to describe interference on spatially distributed antenna elements. Particular attention is paid to the development of algorithms that can be implemented with limited computing resources and work in real time, which is a problem of statistical methods of signal processing.