Electromagnetic spectrum map construction method based on ordinary kriging interpolation

Abstract

The invention belongs to the field of electromagnetic spectrum monitoring, and relates to an electromagnetic spectrum map construction method based on ordinary kriging interpolation. The electromagnetic spectrum map construction method based on ordinary kriging interpolation comprises the steps of: (1), calculating an experimental variation function according to an observation value obtained by asensor; (2), fitting the value of the experimental variation function on discrete h; (3), calculating the ordinary kriging weight and the lagrangian multiplier at the position s<o>; (4), calculating an observation value at the position s<o> without the sensor; and (5), repeating the step (1) to the step (4) till an observation value at any position without the sensor in an area is estimated, wherein the distribution condition of the observation values in the whole area is obtained; and electromagnetic spectrum map construction is completed. By means of the electromagnetic spectrum map construction method provided by the invention, a relatively high-precision electromagnetic spectrum map construction result can be obtained under the conditions of the same sensor number and deployment by utilization of the spatial correlation of monitoring data.

Description

technical field [0001] The invention belongs to the field of electromagnetic spectrum monitoring, and relates to a method for constructing an electromagnetic spectrum map, in particular to a method for constructing an electromagnetic spectrum map based on ordinary kriging interpolation. Background technique [0002] The electromagnetic spectrum map represents the spatial distribution of electromagnetic spectrum information, including signal power, field strength, and channel gain. Taking into account the differences in the spatial distribution of electromagnetic spectrum resources, compared with traditional spectrum sensing methods, electromagnetic spectrum maps are more conducive to improving the utilization of limited spectrum resources. Therefore, in cognitive radio, electromagnetic spectrum management, signal coverage prediction and smart city and other fields have broad application prospects. [0003] Due to the influence of various factors such as cost, number of sens...

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Problems solved by technology

[0006] 1. Indirect construction methods, methods based on compressed sensing, and methods based on dictionary learning rely on information about radiation sources and propagation environments, which are not available in many practical application scenarios;

[0007] 2. The method based on matrix completion, method based on compressed sensing and method based on dictionary learning requires a large number of observations, which requires the dense deployment of a large number of sensors in the region of interest. This deployment method is costly and usually in practical applications hard to accomplish;

[0008] 3. The direct construction method based on the deterministic interpolation method does not consider the correlation between electromagnetic spectrum monitoring data at different locations, resulting in unsatisfactory construction accuracy

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