Method for monitoring interference using signal-to-noise ratio of GNSS terminal real-time observation data

Abstract

The application discloses a method for interference monitoring by using signal-to-noise ratio of GNSS terminal real-time observation data, and belongs to the field of satellite navigation. Based on the method, a satellite navigation terminal can quickly determine whether the GNSS terminal is affected by interference signals without additional spectrum monitoring equipment or calibration of related parameters. The method uses the characteristic that the signal-to-noise ratio of GNSS observation data will be in a stable state in a short time without interference, so that the sliding window mean square deviation index for measuring short-time stability can be used to detect signal-to-noise ratio change abnormalities to realize real-time monitoring of interference, and the number of satellites with abnormal signal-to-noise ratio at the same time in a frequency band is counted to determine whether the navigation signal of the frequency band is interfered.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of satellite navigation, in particular, the direction of satellite navigation interference monitoring, and specifically relates to a method for interference monitoring by using the signal-to-noise ratio of real-time observation data of a global navigation satellite system (GNSS) terminal. BACKGROUND

[0002] With the development of global navigation satellite system (GNSS) technology, it has been widely used in human social production and military applications. However, due to the natural "fragility" of GNSS, it is easy to be intentionally / unintentionally interfered by various electromagnetic signals, which greatly affects the reliability of its positioning, and even directly fails, which will lead to various behaviors that endanger social public safety, such as unmanned, civil aviation, etc. In the traditional case, the monitoring of these interference signals usually uses a special spectrum detection device to detect the spectrum signal of the interference source, so as to realize effective monitoring of the interference signals in the region, but this method needs special equipment, so the economic benefit is not high in the context of normal monitoring demand.

[0003] With the wide use of GNSS terminals in various industries and the continuous development of satellite positioning functions of smart phones, these GNSS terminals, while receiving navigation signals for positioning, speed measurement and time service, also have the ability to sense signals in the navigation frequency band, i.e. the signal strength of observation data, generally known as carrier-to-noise ratio (C / N0) or signal-to-noise ratio (SNR). When there is no interference, the change of SNR is related to the elevation angle, and the change trend is relatively slow; while in real time, SNR will have a significant instantaneous change, such as a significant decrease in suppression interference and a significant increase in a certain amplitude in deception interference. SUMMARY

[0004] The purpose of the present application is to provide a method for interference monitoring of satellite navigation signals by using the SNR of real-time observation data of a GNSS terminal, which solves the problem of effective identification of interference signals by satellite terminals.

[0005] The technical scheme for achieving the purpose of the present application is as follows:

[0006] A method for interference monitoring by using the signal-to-noise ratio of real-time observation data of a GNSS terminal, comprising the following steps:

[0007] Step 1), the GNSS terminal receives satellite observation data in real time;

[0008] Step 2), set a time window, and obtain the signal-to-noise ratio of the observed satellite navigation system of each satellite and each frequency point in the observation period;

[0009] Step 3), continuously calculate the mean square deviation STD of the signal-to-noise ratio of the observation data of the frequency point in the observation period according to the sliding window;

[0010] Step 4), compare the calculated mean square deviation STD with the set threshold value, if it exceeds the threshold value, it is called abnormal;

[0011] Step 5), repeat steps 3) to 4), count the number of abnormal satellites of the frequency point, if the number of abnormal satellites is greater than the set number, the frequency point is interfered, otherwise it is not interfered;

[0012] Step 6), repeat steps 3) to 5) to calculate other frequency points of other observed satellite systems, and real-time interference monitoring of the navigation frequency band.

[0013] Compared with the prior art, the significant advantages of the present application are:

[0014] Without the need for hardware improvement of the existing GNSS navigation terminal and special spectrum equipment for navigation frequency band interference monitoring, it has universality; in addition, the method is simple and easy to implement.

[0015] The present application will be described in further detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 It is a satellite navigation interference monitoring process diagram based on the change of signal-to-noise ratio mean square deviation.

[0017] Figure 2 It is a satellite navigation interference monitoring process diagram based on the change of signal-to-noise ratio mean square deviation. DETAILED DESCRIPTION

[0018] The present application proposes a method for interference monitoring using real-time observation data SNR of GNSS terminal, which can monitor satellite navigation interference in real time, and the method specifically includes:

[0019] The GNSS terminal includes, but is not limited to, satellite navigation reference station, GNSS terminal with satellite navigation positioning, etc. When performing interference monitoring, it should be in a stationary or low-speed motion state, and the surrounding observation environment should be in a stable state. The GNSS terminal receives satellite navigation observation data in real time, calculates the SNR mean square deviation value of each satellite frequency point in the sliding time window, and counts the number of abnormal satellites of the same frequency point to perform interference monitoring.

[0020] For example, Figure 1The data processing flow for interference monitoring based on SNR in this invention is as follows:

[0021] Step 1) The GNSS terminal receives satellite navigation observation data in real time when it is stationary or in low-speed motion.

[0022] Step 2), set the time window Δt and obtain the observation time t. i -Δt to t i The signal-to-noise ratio (SNR) of the observation data of each satellite at each frequency point under the satellite navigation system observed within a time period;

[0023] Step 3) Continuously calculate the standard deviation (STD) of the signal-to-noise ratio (SNR) of the observed data at satellite frequency point f during the observation period using a sliding window.

[0024]

[0025]

[0026] in The frequency point represents the observation time t within the sliding time window Δt. i -Δt to t i The signal-to-noise ratio (STD) of the observed data at satellite frequency point f is as follows. This represents the signal-to-noise ratio of the observed data at frequency point f of satellite s at observation time t, as shown in the attached figure. Figure 2 The time series shown are the SNR (triangle marker), SNR STD (dot marker) with a time window of 30 seconds, and elevation angle (pure line) of the L2 frequency point of G01 satellite.

[0027] Furthermore, satellite navigation systems include GPS, BeiDou Navigation Satellite System, GLONASS, Galileo, QZSS, IRNSS, and other satellite navigation systems; frequencies include GPS L1, L2, L5; BeiDou-2 B1I, B2I, B3I; BeiDou-3 B1I, B3I, B1C, B2a; GLONASS G1, G1a, G2, G2a, G3; Galileo E1, E5a, E5b, E6; QZSS L1, L2, L5, L6; IRNSS L5, and other frequencies.

[0028] Step 4), set the SNR root mean square error change threshold T, and compare it with the result calculated in Step 3). With T, if This is called an anomaly;

[0029] Further, the mean square deviation threshold T is set according to the observation frequency and the time window, for example, when the observation frequency is 1 Hz and the time window is set to 30 seconds, T = 1.0 dB·Hz.

[0030] Step 5), repeat steps 3) to 4) to count the number of abnormal satellites N at the frequency point s If N s ≥ 4, the navigation frequency f is interfered, otherwise it is not interfered.

[0031] Step 6), repeat steps 3) to 5) to calculate other observed frequencies, and perform real-time interference monitoring on the navigation frequency band.

[0032] In summary, the method for real-time interference monitoring using SNR of GNSS terminal observation data provided by the present application utilizes the feature that the observation data SNR will be in a stable state for a short time without interference, and if suddenly interfered, the SNR will instantaneously change, for example, significantly decrease for suppression interference, or increase for deception interference. The mean square deviation index for measuring short-time stability is used to detect abnormalities to perform real-time interference monitoring.

[0033] The above is only an embodiment of the present application, and it should be noted that for those skilled in the art, without departing from the technical principles of the present application, a number of improvements and modifications can be made, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims

1. A method for interference monitoring using real-time observation data of a GNSS terminal, characterized in that, It comprises the following steps: Step 1), the GNSS terminal receives satellite observation data in real time; the GNSS terminal used includes a satellite navigation reference station receiver, a measuring receiver, a positioning-capable smartphone, and a vehicle-mounted receiver; Step 2), set a time window, and obtain the signal-to-noise ratio (SNR) of the observed data of each satellite of each satellite navigation system in the observation time period; the satellite navigation system includes GPS, Beidou satellite global navigation system, GLONASS, Galileo, QZSS, and IRNSS satellite navigation system; the frequency points include GPS L1, L2, L5, Beidou No.2 B1I, B2I, B3I, Beidou No.3 B1I, B3I, B1C, B2a, GLONASS G1, G1a, G2, G2a, G3, Galileo E1, E5a, E5b, E6, QZSS L1, L2, L5, L6, or IRNSS L5; Step 3), continuously calculate the mean square deviation (STD) of the signal-to-noise ratio (SNR) of the observation data of the frequency point in the observation time period according to the sliding window; Step 4), compare the calculated mean square deviation (STD) with the set threshold value, if it exceeds the threshold value, it is called abnormal; the threshold value is set according to the observation frequency and the time window; Step 5), repeat steps 3) to 4), count the number of abnormal satellites at the frequency point, if the number of abnormal satellites is greater than the set number, the frequency point is interfered, otherwise it is not interfered; Step 6), repeat steps 3) to 5) to calculate other frequency points of other observed satellite systems, and monitor the navigation frequency band in real time.

2. The method for interference monitoring using real-time observation data of a GNSS terminal according to claim 1, characterized in that The formula for calculating the signal-to-noise ratio (STD) in step 3) is: wherein is the observed data signal-to-noise ratio of the satellite s at the frequency point f at the observation time t in the sliding time window Δt i - Δt to t i is the observed data signal-to-noise ratio of the satellite s at the frequency point f at the observation time t in the sliding time window Δt is the observed data signal-to-noise ratio of the satellite s at the frequency point f at the observation time t in the sliding time window Δt

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