CN110161537B - Method for detecting Beidou deception jamming based on relative distance of receiver - Google Patents

Abstract

The invention provides a method for detecting Beidou deception jamming based on relative distance of a receiver, which comprises the steps that the receiver respectively receives a real Beidou signal and a pseudo Beidou signal under different relative distances, and experimental data are collected; establishing a model to calculate the relative positioning distance between the two receiving modules; calculating a deviation value of the relative distance of the positioning position of the distributed receiver and the average value under the condition of not being disturbed by deception according to the experimental data; and (4) accumulating errors by using a CUSUM algorithm, and judging the deception jamming. By adopting the common GPS/BD antenna as the deception jamming detection antenna, the cost of deception jamming detection is reduced. The relative distance based on positioning between the receiving modules is used as a judgment condition, and the stability is high. By adopting the CUSUM algorithm, when the continuous error accumulation exceeds the threshold value, the receiver is judged to be subjected to the deception interference, and the misjudgment condition caused by unstable deception interference is reduced.

Description

Method for detecting Beidou deception jamming based on relative distance of receiver

Technical Field

The invention belongs to the field of communication, relates to detection of Beidou deception signals, and particularly provides a method for detecting Beidou deception interference by a distributed receiver. Beidou deception jamming detection method based on distributed receiver

Background

At present, the positioning accuracy of the Beidou navigation system in the Asia-Pacific region is better than 10 meters, the speed measurement accuracy is better than 0.2 m/s, and the time service accuracy is better than 50 nanoseconds. The one-way time service precision and the two-way time service index of the Beidou system are superior to those of the similar foreign systems. In the future, the Beidou navigation system is used for positioning and time service in the fields of traffic, agriculture, forestry, fishery, electric power, finance and the like. However, the civil Beidou receiver is easily subjected to deception interference, so that the Beidou receiver can calculate pseudo-geographic positions and pseudo-local time, and the equipment depending on Beidou time service navigation is damaged.

At present, some methods are proposed in the literature related to the detection of the satellite spoofing interference. There are related documents that propose methods for detecting spoofing interference based on the direction angle of the received signal and the degree of dispersion of the signal-to-noise ratio of the received signal, but these methods have high requirements for the receiving antenna. It is proposed theoretically in the literature that the relative distance between the distributed receivers is 0, which is smaller than the actual physical location of the receivers, and the spoofing interference can be detected based on the relative distance between the distributed receivers. However, this document does not actually simulate the relative distance between outdoor distributed receivers that are subject to spoofing interference, nor does it suggest a specific decision formula for detecting spoofing interference.

Disclosure of Invention

In order to solve the problem of detecting the Beidou deception jamming, the invention discovers that the relative distance between distributed receivers is not 0 as a theoretical value under the deception jamming through experiments, and provides a method for rapidly detecting the deception jamming according to a CUSUM algorithm.

The technical scheme adopted by the invention is a method for detecting Beidou deception jamming based on the relative distance of a receiver, and the method comprises the following steps:

step 1, respectively receiving a real Beidou signal and a pseudo Beidou signal by a receiver under different relative distances, and acquiring experimental data;

step 2, establishing a model to calculate the relative distance between the two receiving modules;

step 3, calculating a deviation value of the relative distance and the average value of the positioning position of the distributed receiver under the condition of not being disturbed by deception according to the experimental data;

and 4, utilizing a CUSUM algorithm to accumulate errors and judging the deception jamming.

Optionally, the modeling calculates a relative distance between two positioning modules, including:

the earth is regarded as an ideal sphere, and the Haversene model keeps 0.5% of precision when estimating the distance between two near points;

longitude and latitude position respectively solved by two receivers

Substituting into the formula (1),

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obtaining a relative position d between the longitude and the latitude, wherein in the formula (1), r is the radius of the earth;

and obtaining the estimated distances of the positioning positions of the different distance receiving modules under the two conditions of not being subjected to deception jamming and being subjected to deception jamming.

Optionally, the using the CUSUM algorithm to perform error accumulation, and the determining the spoofing interference includes:

establishing an error judgment function;

and establishing an error accumulation function by using a CUSUM algorithm.

Optionally, the establishing an error determination function includes:

because the receiver locates the relative distance d' i when not being interfered by deception]The method is stable, and the deviation can not exceed 2m. And when the receiver receives the spoofing interference, d [ i ]]And

the deviation of (a) is relatively large. In formula (4), k is a comparison value, and is set to 4;

in the case of deceptive jamming, the error function value l [ i ] is positive; in the case of no spoofing, the error function value i is negative.

Optionally, the establishing an error accumulation function by using a CUSUM algorithm includes:

CUSUM is used to detect data points where an anomaly has begun to occur in a relatively stable data sequence. According to the formula (5), the error accumulation sum function m (t) starts accumulation from the moment when the error judgment function l [ i ] has a positive value;

setting a threshold value tau, judging that the receiver is subjected to deception interference when the error accumulation function m (t) is more than or equal to tau, and solving an iterative relation of m (t) by a formula (6) for conveniently realizing programming;

the invention has the beneficial effects that:

the invention adopts the common GPS/BD antenna as the deception jamming detection antenna, thereby reducing the cost of deception jamming detection. The relative distance of positioning between the receiving modules is used as a judgment condition, so that the stability is high. By adopting the CUSUM algorithm, when the continuous error accumulation exceeds the threshold value, the receiver is judged to be subjected to the deception interference, and the misjudgment condition caused by unstable deception interference is reduced.

Drawings

Fig. 1 is a Beidou analog signal emission diagram.

FIG. 2 is a big dipper signal simulator SMBV satellite signal setting interface.

Fig. 3 is an experimental picture of true distributed receiving of the beidou signal.

Fig. 4-6 show the relative distances at which the receiving modules are positioned, both spoofed and unscrupulous, when the receiving modules are at a distance of 10m,20m, 40m.

Fig. 7-9 illustrate deviations of relative distances from the average distance of the receiving modules when they are spaced apart 10m,20m,40m without spoofing interference.

FIG. 10 shows the detection effect of the CUSUM algorithm in the case of spoofing interference when the receiving modules are at distances of 10m,20m and 40m.

Detailed Description

The receiver chip of the experiment was a common ATGM332D-5N chip on the market, and the receiving antenna was a common GPS/BD antenna. The big dipper signal simulator of this experiment is SMBV100A, and it can simulate 12 different big dipper signals at most.

The technical scheme adopted by the invention comprises the following steps:

1, receiving Beidou signals at different positions by a receiving antenna under the conditions of no interference and interference respectively, and solving a positioning position;

2, establishing an earth model to calculate the relative distance of the receiver positioning;

calculating an average value of relative distances of the positioning positions of the distributed receiver and a deviation value of the relative distances of the positioning positions of the distributed receiver and the average value under the condition of not being disturbed by deception according to experimental data;

and 4, calculating the average deviation value of the relative position of the receiver positioning and the actual relative position of the receiver. And (4) utilizing a CUSUM algorithm to accumulate errors, and if the error accumulation value is larger than a threshold value, indicating that the receiver is subjected to deception jamming.

Step 1, the receiver respectively receives a real Beidou signal and a pseudo Beidou signal under different relative distances, and experimental data are collected.

In an open outdoor zone, two pairs of Beidou signal receiving modules are used for receiving Beidou signals. And under the condition that the Beidou signal simulator is closed, the NMEA (National Electron Association) data calculated by the receiving module is transmitted to the computer. And then, extracting the positioning longitude and latitude resolved by the Beidou chip from the NMEA data. The real physical relative position between the receiving modules is changed, and the position positioning of the two Beidou signal receiving modules under different physical relative positions can be extracted by the same method. Experiment in the case where the physical relative positions of the receiving modules are 10m,20m and 40m, the receiver is kept receiving data for about 5 minutes, and their positioning positions are extracted from the 5 minutes NMEA data as experimental analysis data, respectively.

And 2, establishing a model to calculate the relative positioning distance of the two receiving modules.

The invention only calculates the distance difference between two points, and does not need to have high requirement on precision. Therefore, the earth can be considered as an ideal sphere. When the Haversene model estimates the distance between two near points, the accuracy of 0.5 percent can be kept, and the requirement of the invention is met.

Longitude and latitude position respectively solved by two receivers

Substituted into formula (1)>

The relative position d between two longitudes and latitudes can be obtained, and in the formula (1), r is the earth radius and can be regarded as 6378.137km.

And analyzing the experimental data to obtain the estimated distances of the positioning positions of the receiving modules at different distances within 5 minutes under the two conditions of no deception interference and deception interference. See fig. 4-6. The following conclusions can be drawn:

1) The actual physical position between two receivers can be estimated more accurately by using the Haverine model, for example, when the relative distance between the receiving modules is 10m,20m and 40m, the estimated position of the Haverine model is about 12m,19m and 39m.

2) And when the receiving module receives the real Beidou signal for positioning, the relative positioning position between the two receivers is stable.

3) In the case of deception jamming, the relative positions of the receiving modules are smaller than the actual positions and do not exceed 10m.

4) In the case of fraudulent interference, the relative positions of the receiving modules may be unstable. For example, at a distance of 15m, the receivers suddenly increase their relative positioning positions at a moment, and then immediately return to the normal relative positioning positions.

And 3, calculating the deviation value of the relative distance and the average value of the positioning position of the distributed receiver under the condition of not being interfered by deception according to the experimental data.

Under the condition that the receivers are not subjected to deception interference, the positioning result is stable, and the relative distance between the distributed receivers is also stable. The deviation d' i of the relative distance d i of the receiver location from the average value at different time instants can be found according to equations (2) and (3).

The probability distribution of d' i is determined as shown in FIGS. 7-9. It can be seen from the figure that when the receivers are spaced at 10m,20m and 40m, their positioning relative distance is stable without fraudulent interference, and the deviation from the average distance value is not more than 2m.

And 4, utilizing a CUSUM algorithm to accumulate errors and judging the deception jamming.

4-1, establishing an error judgment function l [ i ].

Because the receiver locates the relative distance d' i when not being interfered by deception]The method is stable, and the deviation can not exceed 2m. And when the receiver receives the spoofing interference, d [ i ]]And

the deviation of (a) is relatively large. In equation (4), k is a comparison value and can be set to 4.

In the case of deceptive jamming, the error function value l [ i ] is positive; in the case of no spoofing, the error function value i is negative.

4-2, establishing an error accumulation function m (t) by utilizing a CUSUM algorithm.

CUSUM is used to detect data points in a relatively stable data sequence where an anomaly has begun to occur. According to equation (5), the error accumulation sum function m (t) is accumulated from the moment when the error determination function i [ i ] takes a positive value.

And setting a threshold value tau, and judging that the receiver is subjected to deception interference when the error accumulation function m (t) is more than or equal to tau. For the convenience of programming, equation (6) solves the iterative relationship of m (t).

As shown in the figures 1 and 2, the pseudo time of the Beidou satellite simulator for transmitting the Beidou satellite signals and the pseudo position calculated by the pseudo range are set. After the setting is finished, a radio frequency switch of the Beidou satellite simulator is turned on, and the pseudo Beidou satellite signal starts to be transmitted.

As shown in fig. 3, the relative distance between two big dipper receivers is controlled to be 10m,20m and 40m, and then the receiver positioning relative distance under the two conditions of deception interference and un-deception interference is calculated by using a Haversine model respectively to obtain fig. 4-6.

Fig. 7-9 are graphs of probability of deviation degree of positioning relative distance obtained at different distances under the condition that the receiving module is not interfered by cheating. It can be seen from the figure that the relative positioning distance of the receiving module is stable without spoofing interference, and the deviation from the positioning average value is not more than 2m. This lays a good foundation for detecting spoof interference later by using the deviation of the relative distance of the positioning from the average value of the positioning under the undisturbed condition.

FIG. 10 is a diagram of the simulation effect of the CUSUM algorithm on the accumulation of positioning errors. The simulation data is data received at a distance of 10m,20m and 40m in both cases of deception and non-deception interference by a receiver. And ensuring that two receivers receive deception jamming without switching at the same time, and performing data processing by using a CUSUM algorithm to obtain the result of the graph 10. In fig. 10, it can be seen that as the distance increases, the slope of m (t) also increases. Setting the threshold τ =50, spoofing interference can be detected in a short time when the physical distance of the receiver is 40 m.

It should be understood by those skilled in the art that the above embodiments are only for illustrating the present invention and are not to be taken as limiting the present invention, and the changes and modifications of the above embodiments are within the scope of the present invention.

Claims (5)

1. A method for detecting Beidou deception jamming based on relative distance of a receiver is characterized by comprising the following steps:

step 1, respectively receiving a real Beidou signal and a pseudo Beidou signal by a receiver under different relative distances, and acquiring experimental data;

step 2, establishing a model to calculate the relative positioning distance of the two receiving modules;

step 3, calculating a deviation value of the relative distance and the average value of the positioning position of the distributed receiver under the condition of not being disturbed by deception according to the experimental data;

and 4, utilizing a CUSUM algorithm to accumulate errors and judging the deception jamming.

2. The method for detecting Beidou deception jamming based on receiver relative distance according to claim 1, wherein the modeling calculates the relative distance between two receiving module locations, comprising:

the earth is regarded as an ideal sphere, and the Haversene model keeps 0.5% of precision when estimating the distance between two near points;

longitude and latitude position respectively solved by two receivers

Substituting into the formula (1),

obtaining a relative position d between the longitude and the latitude, wherein in the formula (1), r is the radius of the earth;

and obtaining the estimated distances of the positioning positions of the different distance receiving modules under the two conditions of not being subjected to deception jamming and being subjected to deception jamming.

3. The method for detecting Beidou deception jamming based on receiver relative distance according to claim 1, wherein the error accumulation is performed by using CUSUM algorithm, and the determining deception jamming comprises:

establishing an error judgment function;

and establishing an error accumulation function by using a CUSUM algorithm.

4. The method for detecting Beidou deception jamming based on receiver relative distance according to claim 3, wherein the establishing an error judgment function comprises:

because the receiver locates the relative distance d' i when not being interfered by deception]Is stable, the deviation will not exceed 2m, and when the receiver receives the deception jamming, d [ i]And

is large, in formula (4), k is a comparison value, and is set to be 4;

in the case of deceptive jamming, the error function value l [ i ] is positive; in the case of no spoofing, the error function value i is negative.

5. The method for detecting Beidou deception jamming based on receiver relative distance according to claim 1, wherein the establishing an error accumulation function by using CUSUM algorithm comprises:

CUSUM is used for detecting data points which start to generate abnormity in a certain relatively stable data sequence, and accumulating the error accumulation sum function m (t) from the moment when the error judgment function l [ i ] generates positive values according to a formula (5);

setting a threshold value tau, judging that the receiver is subjected to deception interference when the error accumulation function m (t) is more than or equal to tau, and solving an iterative relation of m (t) by a formula (6) for conveniently realizing programming;

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