Background: The use of passive matrix radiometric sensors of the millimeter wave range in aircraft navigation systems, which make it possible to form a radiometric image of a ground navigation object under conditions of high-speed flight of aircraft, is one of the effective ways to ensure high accuracy in measuring the coordinates of objects and, ultimately, leads to an increase in the probability of positioning aircraft [1]. In work [2], analytical relationships were obtained and quantitative estimates of the accuracy of positioning of aircraft equipped with a matrix radiometric navigation system were made. It is shown that the use of matrix radiometric sensors makes it possible to realize the required high (up to units - tens of meters) positioning accuracy of high-speed aircraft. Objectives: The purpose of this article is to develop a method for increasing the accuracy of a radiometric correlation - extreme system based on the use of a matrix radiometric millimeter-wave receiver with channel compaction. Materials and methods: In this paper, we used the method of linear multiplexing with channel separation according to the waveform using orthogonal Walsh functions. In this case, the sensitivity for each channel corresponds to the sensitivity of the modulation radiometer, and in comparison with the sensitivity of the compensation radiometer, it decreases by about two times. Taking into account the orthonormality of the Walsh functions, the signal at the output of each channel is proportional to the intensity (power) of the signal at the input of this channel. Results: In this work, it is shown that the optimal number of combined channels is a multiple . The analysis of the results of the calculations shows that the combination of 64 channels into one amplifier-conversion path leads to an increase in inter-channel interference and, as a consequence, to a deterioration in the sensitivity of each channel. Conclusions: In this case, it is expedient to limit the number of channels to be sealed per one amplifying-converting path. So, when 16 channels are combined into one path, the sensitivity of each channel remains quite high: about 1 K – for a super heterodyne radiometric receiver, and less than 1 K – for a direct amplification radiometric receiver. In this case, the number of amplifying-conversion paths with the total number of channels in the matrix 64 is equal to four.

Background: Improving the positioning accuracy of passive radiometric correlation-extreme navigation systems (RM CENS) of aircraft (AC) by landmarks depends on the ability of information RM sensors of systems to form two-dimensional images of ground objects in real time. The use of matrix RM sensors, which are based on multichannel RM receivers of the millimeter wave range (MMW), makes it possible to realize the required speed of the CENS Objectives: The aim of the work is to optimize the number of multiplexed channels per one amplifying-converting path of a multi-channel RM receiver with linear multiplexing and separation of channels according to the form of signals. Materials and methods: As an optimization criterion in this work, it is proposed to use the gain in sensitivity obtained as a result of the use of a multichannel RM receiver with linear multiplexing and signal waveform separation in comparison with the sensitivity of a RM receiver with time division multiplexing. Results: As a result of the analysis of the process of functioning of a multichannel RM receiver with time division multiplexing in this work a relation was obtained for the sensitivity of an individual channel of a RM receiver with time division multiplexing. Conclusions: It can be concluded that it is optimal to create a matrix RM receiver based on combining 16 RM channels of the superheterodyne type into one amplifier-conversion path. In this case, the total number of amplifying-converting paths is equal to four. The sensitivity of each channel remains high enough.

Relevance. Spline interpolation is used to improve the accuracy of correlation-extreme navigation systems. A two-stage algorithm for combining images in correlation-extreme navigation systems is proposed. At the first stage, the surface of the decision function of the algorithm is constructed in the vicinity of its extremum using a quadratic interpolator by six points and its Gaussian curvature and extremum coordinates are estimated. These parameters are used to determine the optimal value of the parameter of the cubic spline interpolator used in the second stage in order to refine the rough estimate of the coordinates and improve the positioning accuracy of the navigation system. Purpose of the work: The purpose of the work is to develop an algorithm for aligning images in correlation-extreme navigation systems, which makes it possible to realize a cubic spline parameter close to the optimal value for each of the possible shifts of the current image relative to the reference image and, as a result, to increase the accuracy of determining the coordinates. Materials and methods. In correlation-extreme navigation systems, the coordinates of the aircraft are determined by calculating the mutual shift of the current image obtained using the sensor of the Earth's physical field and the reference image, which is known in advance. At the same time, the alignment accuracy of discrete current and reference images, which are usually used in practice, does not exceed half a pixel. Therefore, the problem of improving the accuracy of navigation systems is of great importance. One of the possible ways to solve this problem is to use methods for approximating the decision function of the image alignment algorithm in the vicinity of its global maximum.Results: To illustrate the gain in the accuracy of the positioning of navigation systems, statistical tests of the algorithm with a 6-point interpolator and the above-described two-stage procedure for minimizing the decision function containing spline interpolation at the second stage were carried out. A typical image was used as a reference image. The coordinates of the center of the current and reference images were played randomly in accordance with the two-dimensional normal distribution law, the average value of which coincided with the center of the reference image; the standard deviation is also found. Then the current image was formed. The constructed current image was noisy with additive white Gaussian noise with zero mean value and the same standard deviation for each element . Image alignment was assumed to be correct if the following conditions were met: , where – is the shift estimate generated by the algorithm. Then, the algorithms were repeatedly run with different realizations of the noise component of the current image, and the dependences of the root-mean-square error in each direction on the mean-square value were plotted . The figures in the article show the dependencies for the algorithm with a 6-point interpolator (upper curve) and for a two-stage algorithm (lower curve). Analysis of the graphs allows us to conclude that the second algorithm wins in the accuracy of determining the coordinates of the shift by about 5 times. The dependencies for both algorithms practically coincide with those shown in the figure. It should be noted the weak dependence of the positioning accuracy on the change in the parameter in the area . Conclusions: It is shown that the optimal value of the parameter of the cubic spline interpolator depends to a lesser extent on the magnitude of the local shift of the images and, to a greater extent, on the correlation interval of the reference image in the vicinity of the image alignment point, which is proposed to be estimated using the Gaussian curvature parameter.