CN-121186820-B - Beidou signal interfered active identification method

CN121186820BCN 121186820 BCN121186820 BCN 121186820BCN-121186820-B

Abstract

The invention relates to the technical field of satellite navigation and communication, and discloses a Beidou signal interfered active recognition method which comprises the steps of collecting Beidou signals, electromagnetic environment parameters and equipment running state data in real time, extracting a characteristic parameter set, constructing an interference analysis module and a self-adaptive learning model, outputting an interference level judging result and adjusting a positioning compensation strategy. According to the method, by introducing the self-adaptive learning model and combining the Beidou signal characteristic parameters, the electromagnetic environment characteristic parameters and the equipment state characteristic parameters, whether the Beidou signal is interfered or not can be effectively identified, and the positioning compensation strategy is adjusted according to the interference level judgment result. The method abandons the traditional fixed threshold analysis logic, can adapt to complex and changeable electromagnetic environments, remarkably improves the accuracy and response speed of interference identification, and is suitable for the actual requirements of power inspection scenes.

Inventors

SONG TAO
ZHAO MINGCHEN
ZHANG HENG

Assignees

北京安心易维科技有限公司

Dates

Publication Date: 20260512
Application Date: 20250925

Claims (7)

1. The Beidou signal interfered active identification method is characterized by comprising the following steps of: S1, acquiring Beidou signals received by terminal equipment in real time; s2, acquiring electromagnetic environment parameter data in the area; s3, collecting the running state data of the equipment in the area; S4, extracting the collected Beidou signal, electromagnetic environment parameters and equipment running state data, and processing to obtain a characteristic parameter set; S5, constructing an interference analysis module; s6, obtaining interference characteristic indexes in the current period according to the constructed interference analysis module; s7, taking an interference characteristic index and a characteristic parameter set in the current period as input to construct a self-adaptive learning model; s8, outputting an interference level judgment result through the self-adaptive learning model; s9, adjusting a positioning compensation strategy of the terminal equipment according to the interference level judging result; In the step S4, the processing to obtain the characteristic parameter set specifically includes: s4.1, extracting Beidou signal parameter data in the area; s4.2, combining the maximum value and the minimum value of the signal-to-noise ratio of the Beidou signal in the area, introducing a dynamic floating range, and generating a signal quality characteristic; s4.3, extracting electromagnetic environment parameter data in the area; S4.4, combining the maximum electromagnetic field intensity value and the minimum electromagnetic field intensity value of all monitoring points, introducing a dynamic floating range, and generating electromagnetic environment characteristics; S4.5, combining the maximum noise power density value and the minimum noise power density value of all the monitoring frequency bands, introducing a dynamic floating range, and generating noise characteristics; s4.6, extracting the running state data of the equipment in the area; s4.7, dividing a plurality of time windows, and carrying out segmentation processing on the running state data of the equipment by using the divided time windows; S4.8, combining the equipment operation state data in at least three time windows to generate equipment state characteristics; In the S5, the interference analysis module comprises a signal characteristic extraction unit, an interference pattern matching unit and an interference verification unit, wherein the signal characteristic extraction unit is electrically connected with the interference pattern matching unit; The interference pattern matching unit is used for matching possible interference patterns and generating a preliminary interference characteristic index according to the combination of the electromagnetic environment characteristic and the noise characteristic of the signal characteristic vector, and the interference verification unit is used for comparing and verifying the preliminary interference characteristic index with a reference index in a historical interference database, wherein the verification formula is as follows: wherein For the minimum lower-limit float value, If the verification formula is satisfied, the preliminary interference characteristic index is confirmed, otherwise, the preliminary interference characteristic index is invalid.
2. The method for actively recognizing the interference of the Beidou signal according to claim 1, wherein in the step S1, carrier frequency offset, signal to noise ratio and signal receiving strength of the Beidou signal are used as main acquisition parameters.
3. The method for actively recognizing the Beidou signal according to claim 1, wherein in the step S2, the electromagnetic environment parameter data at least comprise electromagnetic field intensity distribution, electromagnetic noise spectrum density and electromagnetic radiation direction characteristics in an area, the parameter data of the electromagnetic field intensity distribution comprise maximum electromagnetic field intensity values and minimum electromagnetic field intensity values of all monitoring points, and the parameter data of the electromagnetic noise spectrum density comprise maximum noise power density values and minimum noise power density values of all monitoring frequency bands.
4. The method for actively recognizing the Beidou signal according to claim 1, wherein in the step S3, the equipment operation state data at least comprises current position coordinates of the terminal equipment, motion track deviation and health state data of sensors inside the equipment.
5. The method for actively identifying the Beidou signal interference according to claim 1, wherein in the step S7, the construction of the adaptive learning model specifically comprises the following steps: S7.1, firstly receiving a preliminary interference characteristic index, a Beidou signal characteristic parameter, an electromagnetic environment characteristic parameter and a device state characteristic parameter in the area, and taking the preliminary interference characteristic index, the Beidou signal characteristic parameter, the electromagnetic environment characteristic parameter and the device state characteristic parameter as input data; S7.2, extracting positioning precision change data in at least five time windows as a reference; S7.3, substituting the extracted positioning precision change data into the self-adaptive learning model; s7.4, determining target optimization parameters, substituting the target optimization parameters into the self-adaptive learning model, and performing iterative training; s7.5, carrying out data analysis and pattern recognition through the self-adaptive learning model, and outputting an interference level judgment result; and S7.6, carrying out reliability evaluation on the outputted interference level judging result.
6. The method for actively identifying the Beidou signal interference according to claim 5, wherein in the evaluation of the credibility of the interference level judgment result, a high credibility value and a low credibility value are respectively confirmed through the combination analysis of two evaluation modes, and a calculation formula of the high credibility value is as follows: Wherein the method comprises the steps of Expressed as a signal-to-noise ratio characteristic value of the Beidou signal, EMF is expressed as electromagnetic field intensity characteristic values of a plurality of monitoring points, And Are all defined weight coefficients, and And And then calculating a low confidence value, wherein the specific low confidence value has the following calculation formula: Wherein the method comprises the steps of Represented as a device state characteristic value, Represented as a preliminary disturbance characteristic index, And Are all defined weight coefficients, and And If the high reliability value and the low reliability value satisfy the verification formula, determining the comprehensive reliability according to the first reliability value and the second reliability value The specific formula is as follows: 。
7. The method for actively recognizing the Beidou signal interfered according to claim 1, wherein in the step S9, an interference level judging result is output through the self-adaptive learning model, and a positioning compensation strategy of the terminal equipment is adjusted according to the output interference level judging result, and the specific adjustment mode comprises the steps of correcting a receiving sensitivity threshold value of the Beidou signal, switching to a standby navigation mode and adjusting equipment movement track planning.

Description

Beidou signal interfered active identification method Technical Field The invention relates to the technical field of satellite navigation and communication, in particular to an active identification method for Beidou signal interference. Background The Beidou satellite navigation system is a global satellite navigation system independently researched and developed in China, and can provide all-weather and high-precision positioning, navigation and time service for users. The system is widely applied to a plurality of fields such as transportation, electric power inspection, agricultural monitoring, emergency rescue and the like. In the power inspection, the Beidou signal provides important positioning support for the terminal equipment, so that the equipment can accurately reach a target position and complete tasks. However, due to electromagnetic interference or human factors in a complex environment, the Beidou signal may be interfered to a certain extent, so that positioning accuracy is affected and even a task failure is caused. Therefore, how to effectively identify whether the beidou signal is interfered becomes a problem to be solved. In the prior art, the detection method for Beidou signal interference mainly depends on simple judgment of signal intensity or an analysis strategy based on a fixed threshold value. Although these methods can reflect the variation of signal quality to some extent, they often fail to sufficiently consider the diversity and dynamics of the interference sources in the actual environment. In addition, the traditional detection means generally lack active recognition capability, and early warning cannot be performed in time in the early stage of interference occurrence, so that subsequent processing is delayed, and the continuity and reliability of the power inspection task are affected. Although the anti-interference Beidou signal receiving device and the anti-interference Beidou signal receiving method enhance the stability of signal reception to a certain extent, the identification process of the anti-interference Beidou signal receiving device and the anti-interference Beidou signal receiving method depend on fixed processing logic and lack optimal design for an electric power inspection scene, so that problems of low identification efficiency, low response speed and the like possibly exist when the anti-interference Beidou signal receiving device and the anti-interference Beidou signal receiving method face a complex electromagnetic environment, and normal operation of terminal equipment is affected. Disclosure of Invention The invention aims to provide an active identification method for Beidou signal interference, which solves the problem that in the background technology, in the process of detecting Beidou signal interference, the interference is often dependent on simple signal intensity judgment or a fixed threshold analysis strategy. The traditional methods fail to fully consider the diversity and the dynamic property of interference sources in a complex environment, and lack active recognition capability, and early warning cannot be performed in time in the early stage of interference occurrence, so that the continuity and the reliability of an electric power inspection task are affected. In order to solve the technical problems, the invention provides the following technical scheme: A Beidou signal interfered active identification method comprises the following steps: collecting Beidou signals received by terminal equipment in real time; collecting electromagnetic environment parameter data in the area; collecting the running state data of the equipment in the area; extracting the collected Beidou signal, electromagnetic environment parameters and equipment running state data, and processing to obtain a characteristic parameter set; Constructing an interference analysis module; According to the interference characteristic index in the current period obtained by the constructed interference analysis module; Taking the interference characteristic index and the characteristic parameter set in the current period as input to construct a self-adaptive learning model; outputting an interference level judgment result through the self-adaptive learning model; and adjusting a positioning compensation strategy of the terminal equipment according to the interference level judging result. Preferably, in the real-time acquisition of the Beidou signal, the carrier frequency offset, the signal to noise ratio and the signal receiving intensity of the Beidou signal are used as main acquisition parameters. Further, the signal acquisition module is used for acquiring Beidou signal parameters received by the terminal equipment in real time. The module mainly collects carrier frequency offset, signal to noise ratio and signal receiving strength of the Beidou signals and transmits the data to the interference analysis module. The output end of the signal acquisition module is connect