An analysis the mutual influence of channels in radiotechnical information-measuring system

Abstract

The development of new radiotechnical information-measuring systems (IMSs) of the ground control complex of flying objects should be aimed at increasing their capabilities for accurate and reliable control of signals navigation parameters. This is especially important in a time-limited communication session, as well as for ensuring the operational control of the trajectories of ballistic objects during their flight along unequipped routes.In recent years, wideband noise-like signals (WNLSs) are often used in radio systems ‒ complex discrete signals, modulated by a harmonious signal in frequency, phase and amplitude by a pseudo-random sequence code. The use of the WNLSs is explained by a number of their properties: better noise immunity and concealment, greater accuracy in measuring the speed and range of moving objects, the prospect of more efficient use of such signals in the allowed frequency ranges, and the possibility of their multipath propagation.IMSs with WNLSs have several advantages: increased noise immunity, secrecy, the ability to measure the motion parameters of an aircraft object with one signal and transmit information, sufficient accuracy and high reliability of in­formation transfer. In the future, this may lead to the construction of unified, mobile information-measuring systems, the tactical and technical characteristics of which will meet modern requirements. However, the main reasons preventing the wider implementation of complex pseudo-random signals in the practice of radio engineering IMSs are the difficulties as­sociated with their optimal processing.In this paper, the analysis of information-measuring systems with wideband noise-like signals was performed to determine the degree of mutual influence of the channels, when filtering interrelated parameters of signal. It is established, that the errors caused by the mutual influence of the channels are minimal if the parameter estimate coincides with its true value, and there are no divergences on the filtered parameter. Thus, the filtering accuracy of each of the parameters depends on the degree of their correlation, on the signal-to-noise ratio, and on the steepness of autocorrelation function the input signal complex envelope.