CN115079089A - Differential correction-based non-cooperative unmanned aerial vehicle accurate positioning method and device - Google Patents

Differential correction-based non-cooperative unmanned aerial vehicle accurate positioning method and device Download PDF

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CN115079089A
CN115079089A CN202210654153.2A CN202210654153A CN115079089A CN 115079089 A CN115079089 A CN 115079089A CN 202210654153 A CN202210654153 A CN 202210654153A CN 115079089 A CN115079089 A CN 115079089A
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刘昕
孙胜
宫法明
吴春雷
杨大伟
赵庆齐
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China University of Petroleum East China
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Abstract

The invention provides a differential correction-based non-cooperative unmanned aerial vehicle accurate positioning method and device. The method comprises the steps of defining 3-dimensional distance difference of correction points to construct a distance difference space model; acquiring self-flying data of the unmanned aerial vehicle of our party in advance, acquiring the precise position of the unmanned aerial vehicle and the TDOA distance difference, and realizing systematic positioning correction of a distance difference space model; after the invasion of the non-cooperative unmanned aerial vehicle is discovered, the precise position of the non-cooperative unmanned aerial vehicle is corrected in real time through the accompanying flight of the unmanned aerial vehicle of one party, a flight sequence sample set is constructed by using collected self-flight data and flight data of the non-cooperative unmanned aerial vehicle, a GRU sequence prediction model is constructed, the unmanned aerial vehicle self-flight sequence sample carrying a soft module of one party is used as a training set, the GRU sequence prediction model is trained, the flight sequence of the non-cooperative unmanned aerial vehicle is used as a prediction set, the decision-making level fusion is carried out on the prediction result of the GRU model and the assimilation positioning result corrected in real time, and the precise coordinate of final positioning is obtained.

Description

Differential correction-based non-cooperative unmanned aerial vehicle accurate positioning method and device
Technical Field
The invention relates to a non-cooperative unmanned aerial vehicle accurate positioning method, in particular to a non-cooperative unmanned aerial vehicle accurate positioning method based on differential correction.
Background
In recent years, unmanned aerial vehicles have the characteristics of flexibility, rich functions, easiness in operation and the like, and are widely used in military, civil and industrial fields such as battlefields, aerial photography, agriculture, surveying and mapping, disaster relief and the like, so that the market of the unmanned aerial vehicles is increased explosively. When the number of unmanned aerial vehicles is rapidly increased, the unmanned aerial vehicles fly in violation and attack events of the unmanned aerial vehicles continuously occur, so that unmanned aerial vehicle defense is concerned extensively. The passive accurate positioning of the non-cooperative unmanned aerial vehicle is realized, is a necessary measure for unmanned aerial vehicle defense, is influenced by weather, environment and interference waves, has larger positioning error of the non-cooperative unmanned aerial vehicle in the traditional positioning method, reduces the positioning error by applying the prior art base under the defense space environment, and is a hotspot problem of current research.
Aiming at the problem of passive positioning of the unmanned aerial vehicle, an antenna array is generally used for receiving signals of the unmanned aerial vehicle, which are communicated with a ground station or a remote controller, and the unmanned aerial vehicle is positioned through an array signal processing algorithm, so that the acting distance can reach 3km, and the requirements of most occasions can be met. The multi-station passive positioning determines a plurality of positioning curves (or curved surfaces) by means of some information (time difference, angle and the like), and the target position can be obtained by solving the intersection points of the curves (or curved surfaces). There are currently 3 mature mainstream methods: based on signal strength indication (RSSI) positioning, determining the distance between two ends according to a signal attenuation model between a signal emission source and a receiving end, and further positioning through multiple receiving points; calculating the position of a signal source by comparing absolute time differences between the arrival of a signal from a transmission source at each receiving end based on a time difference of arrival (TDOA) location of the signal and converting the absolute time differences into distance differences; based on direction of arrival estimation (DOA) localization, the bearing of the signal source is estimated from the phase difference of the signal incident from the signal source to the array antenna. Because unmanned aerial vehicle signal receives the interference of environment and other signals, the error of passive location is minimum 20m at present, is difficult to reach the needs of accurate striking and counter-measure.
Based on the problems in the research, the invention provides a non-cooperative unmanned aerial vehicle accurate positioning method and device based on differential correction. The method comprises the steps of defining 3-dimensional distance difference of correction points to construct a distance difference space model; acquiring self-flying data of the unmanned aerial vehicle of one party in advance, acquiring the accurate position of the unmanned aerial vehicle and the TDOA distance difference, and realizing systematic positioning correction of a distance difference space model; after the non-cooperative unmanned aerial vehicle is discovered to invade, the non-cooperative unmanned aerial vehicle flies by the unmanned aerial vehicle of the same party, the accurate position of the non-cooperative unmanned aerial vehicle is corrected in real time, and the accurate positioning of the unmanned aerial vehicle is realized.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a non-cooperative unmanned aerial vehicle accurate positioning method and device based on differential correction. In the defense area, longitude and latitude coordinate correction points are arranged at intervals according to a specific space to form a space grid, 6-dimensional space position representation of the correction points is defined and used for accurately resolving the three-dimensional coordinates and 3-dimensional difference data of the correction points, and therefore a space difference model containing all the correction points is constructed. Aiming at the selected defense area, arranging that the unmanned aerial vehicle of one party tries to fly in advance and returns accurate positioning data, resolving a 3-dimensional difference value of a correction point according to a space difference value between the accurate position of the unmanned aerial vehicle and TDOA positioning data of a defense system, establishing a space model correction and difference positioning database, and realizing the calibration of a systematic space position model. By applying the corrected systematic space model, an accurate positioning scheme combining static correction in advance and real-time difference of a defense field is researched, and the positioning accuracy of the non-cooperative unmanned aerial vehicle is improved.
The technical scheme adopted by the invention is as follows:
a non-cooperative unmanned aerial vehicle accurate positioning method and device based on differential correction comprises the following steps:
A. and constructing a distance difference space model. Setting distributed time difference positioning space range, setting one coordinate point in each direction at interval of 1m in space coordinate system, marking its position coordinate with accurate longitude and latitude and height, all the correction points forming oneA spatial grid. Because of the difference of space environment and the interference of various signals, the coordinate of the unmanned aerial vehicle given by the TDOA positioning system has different errors at each position, 3 distance difference dimensions are added for each correction point to form a 6-dimensional position coordinate, and the position coordinate of the ith correction point is
Figure RE-GDA0003754407570000021
The distance difference model is used for storing accurate 3-dimensional coordinates and 3-dimensional difference data of calculated correction points, and all 6-dimensional coordinate points at intervals of 1m in a correction space form a distance difference space model.
B. A differential-based systematic spatial model location correction. The unmanned aerial vehicle carrying the soft module in one part is released to fly automatically in the defense space, the GPS accurate position of the unmanned aerial vehicle is returned in the flying process, and the flying track covers each grid of the distance difference space model through multiple rounds of self-flying. Aiming at each correction point in the space model, acquiring a plurality of accurate positions returned in 4 grids around the correction point and TDOA coordinates corresponding to each position, and respectively marking as P 1 ，...，P i ，...，P n And P' 1 ，...，P′ i ，...，P′ n In which P is i Is marked as an accurate position
Figure RE-GDA0003754407570000022
Location P 'of TDOA System location' i Is recorded as (x' i ，y′ i ，z′ i ). Based on the precise position and the TDOA system coordinate, calculating the 3-dimensional distance difference of the middle positioning points of the grid according to the formulas (1) to (3), which are respectively marked as d x ，d y ，d z 。
Figure RE-GDA0003754407570000023
Figure RE-GDA0003754407570000024
Figure RE-GDA0003754407570000025
D of each correction point is obtained according to calculation x ，d y ，d z And updating the distance difference value of each correction point in the distance difference space model to realize systematic positioning correction of the whole space model.
C. Non-cooperative unmanned aerial vehicle accurate positioning based on real-time correction. When the TDOA system detects the signal of the invading unmanned aerial vehicle, the real-time TDOA position of the invading unmanned aerial vehicle is calculated and taken as the initial position P 0 (x′ 0 ，y′ 0 ，z′ 0 ). Putting the unmanned aerial vehicle into a distance difference space model, and if the position falls on a correction point, directly calculating the correction position of the non-cooperative unmanned aerial vehicle according to the current 3-dimensional distance difference value of the correction point
Figure RE-GDA0003754407570000031
If the position is located at the non-correction point, taking the 3-dimensional distance difference value of 4 correction points of the grid where the position is located, calculating the distance difference of the position according to the formulas (4) - (6), and obtaining the system static correction position of the position
Figure RE-GDA0003754407570000032
Figure RE-GDA0003754407570000033
Figure RE-GDA0003754407570000034
Figure RE-GDA0003754407570000035
And releasing the unmanned aerial vehicle of the owner to fly together according to the static correction position of the system, returning the self accurate GPS position by the unmanned aerial vehicle of the owner when the unmanned aerial vehicle is close to the non-cooperative unmanned aerial vehicle (defined as a cross point within the range of 30 cm), calculating the distance difference between the accurate position of the unmanned aerial vehicle of the owner and the static correction position of the system, taking the distance difference as the distance difference of the non-cooperative unmanned aerial vehicle, and correcting the accurate position of the non-cooperative unmanned aerial vehicle in real time. In the accompanying flight process, the unmanned aerial vehicle of one party is close to the non-cooperative unmanned aerial vehicle for many times, and each intersection point is used as an assimilation point, so that the non-cooperative unmanned aerial vehicle can be continuously updated and positioned in real time. A flight sequence sample set is constructed with the collected self-flight data and non-cooperative drone flight data, each sample being represented as (TDOA location, precise location). And (3) constructing a GRU sequence prediction model, taking an unmanned aerial vehicle self-flying sequence sample carrying a soft module in one party as a training set, training the GRU sequence prediction model, taking a flight sequence of a non-cooperative unmanned aerial vehicle as a prediction set, and performing decision-making level fusion on a prediction result of the GRU model and an assimilation positioning result corrected in real time to obtain a final positioning accurate coordinate.
The TDOA positioning system in step a is a method for positioning by using time difference of arrival. And each time the positioning tag transmits a positioning broadcast signal, and the coordinates of the tag are calculated according to the time difference between the signal and each positioning base station and the known positions of all the base stations.
The soft module in the step B is firmware programming code used for embedding identity information of the unmanned aerial vehicle.
The GRU in the step C is a neural network, the concepts of a reset gate and an update gate are introduced, the information flow between cells in the neural network is controlled and managed through a gate control mechanism, the past information is memorized, and some unimportant information is selectively forgotten, so that the problem of gradient in long-term memory and back propagation is solved.
On the other hand, the invention provides a non-cooperative unmanned aerial vehicle accurate positioning device based on differential correction, which comprises the following modules:
the distance difference space model construction module comprises: setting a distributed time difference positioning space range, setting a coordinate point, called a correction point, in each direction at an interval of 1m in a space coordinate system, marking the position coordinates of the coordinate points by using accurate longitude and latitude and height, and forming a space grid by all the correction points. Adding 3 distance difference dimensions for each correction point to form 6-dimensional position coordinates, and locating the ith correction pointSet coordinate as
Figure RE-GDA0003754407570000036
The distance difference model is used for storing accurate 3-dimensional coordinates and 3-dimensional difference data of calculated correction points, and all 6-dimensional coordinate points at intervals of 1m in a correction space form a distance difference space model.
The space model positioning correction module: aiming at each correction point in the space model, acquiring a plurality of accurate positions of self-flying return of the unmanned aerial vehicle in 4 grids around the correction point and TDOA coordinates corresponding to each position, and respectively recording as P 1 ，...，P i ，...，P n And P' 1 ，...，P′ i ，...，P′ n In which P is i Is marked as an accurate position
Figure RE-GDA0003754407570000041
Position P 'of TDOA system location' i Is recorded as (x' i ，y′ i ，z′ i ). Calculating the 3-dimensional distance difference of the middle positioning points of the grid according to the formulas (1) to (3), and respectively recording the 3-dimensional distance difference as d x ，d y ，d z . D of each correction point is obtained according to calculation x ，d y ，d z And updating the distance difference value of each correction point in the distance difference space model to realize systematic positioning correction of the whole space model.
Non-cooperative unmanned aerial vehicle accurate positioning module: when the TDOA system detects the signal of the invading unmanned aerial vehicle, the real-time TDOA position of the invading unmanned aerial vehicle is calculated and taken as the initial position P 0 (x′ 0 ，y′ 0 ，z′ 0 ). Putting the unmanned aerial vehicle into a distance difference space model, and if the position falls on a correction point, directly calculating the correction position of the non-cooperative unmanned aerial vehicle according to the current 3-dimensional distance difference value of the correction point
Figure RE-GDA0003754407570000042
If the position is located at the non-correction point, taking the 3-dimensional distance difference value of 4 correction points of the grid where the position is located, calculating the distance difference of the position according to the formulas (4) - (6), and obtaining the system static correction position of the position
Figure RE-GDA0003754407570000043
And releasing the unmanned aerial vehicle of the my party to fly together according to the static correction position of the system, returning the accurate GPS position of the unmanned aerial vehicle of the my party when the unmanned aerial vehicle of the my party approaches to the non-cooperative unmanned aerial vehicle (the unmanned aerial vehicle of the my party is defined as a cross point within the range of 30 cm), calculating the distance difference between the accurate position of the unmanned aerial vehicle of the my party and the static correction position of the system, taking the distance difference as the distance difference of the non-cooperative unmanned aerial vehicle, and correcting the accurate position of the non-cooperative unmanned aerial vehicle in real time. In the accompanying flight process, the unmanned aerial vehicle of one party is close to the non-cooperative unmanned aerial vehicle for many times, and each intersection point is used as an assimilation point, so that the non-cooperative unmanned aerial vehicle can be continuously updated and positioned in real time. A flight sequence sample set is constructed with the collected self-flight data and non-cooperative drone flight data, each sample being represented as (TDOA location, precise location). And (3) constructing a GRU sequence prediction model, taking an unmanned aerial vehicle self-flying sequence sample carrying a soft module in one party as a training set, training the GRU sequence prediction model, taking a flying sequence of a non-cooperative unmanned aerial vehicle as a prediction set, and performing decision-level fusion on a prediction result of the GRU model and an assimilation positioning result corrected in real time to obtain accurate coordinates of final positioning.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is an execution flow chart of a non-cooperative unmanned aerial vehicle accurate positioning method based on differential correction according to the present invention.
FIG. 2 is a distance difference-based systematic spatial model positioning calibration chart of the present invention.
FIG. 3 is a non-cooperative UAV position enhancement diagram based on real-time correction according to the present invention
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Example one
The basis of this embodiment lies in, in current unmanned aerial vehicle positioning technology, traditional approach is great to non-cooperative unmanned aerial vehicle positioning error, can't pinpoint non-cooperative unmanned aerial vehicle position and carry out unmanned aerial vehicle defense. Therefore, the non-cooperative unmanned aerial vehicle position is accurately positioned by constructing a distance difference space model, updating the positioning point distance difference through a static system and dynamically updating the positioning point distance difference in real time.
Firstly, setting a distributed time difference positioning space range, setting a coordinate point, called a correction point, in each direction at an interval of 1m in a space coordinate system, marking the position coordinate of the coordinate point by using accurate longitude and latitude and height, and forming a space grid by using all the correction points. Because of the difference of space environment and the interference of various signals, the coordinate of the unmanned aerial vehicle given by the TDOA positioning system has different errors at each position, 3 distance difference dimensions are added for each correction point to form a 6-dimensional position coordinate, and the position coordinate of the ith correction point is
Figure RE-GDA0003754407570000051
The distance difference model is used for storing accurate 3-dimensional coordinates and 3-dimensional difference data of calculated correction points, and all 6-dimensional coordinate points at intervals of 1m in a correction space form a distance difference space model.
The unmanned aerial vehicle carrying the soft module in one part is released to fly automatically in the defense space, the GPS accurate position of the unmanned aerial vehicle is returned in the flying process, and the flying track covers each grid of the distance difference space model through multiple rounds of self-flying. Aiming at each correction point in the space model, acquiring a plurality of accurate positions returned in 4 grids around the correction point and TDOA coordinates corresponding to each position, and respectively marking as P 1 ，...，P i ，...，P n And P' 1 ，...，P′ i ，...，P′ n In which P is i Is marked as an accurate position
Figure RE-GDA0003754407570000052
Location P 'of TDOA System location' i Is recorded as (x' i ，y′ i ，z′ i ). Based on the precise position and the TDOA system coordinate, calculating the 3-dimensional distance difference of the middle positioning points of the grid according to the formulas (1) to (3), which are respectively marked as d x ，d y ，d z . D of each correction point is obtained according to calculation x ，d y ，d z And updating the distance difference value of each correction point in the distance difference space model to realize systematic positioning correction of the whole space model.
When the TDOA system detects the signal of the invading unmanned aerial vehicle, the real-time TDOA position of the invading unmanned aerial vehicle is calculated and taken as the initial position P 0 (x′ 0 ，y′ 0 ，z′ 0 ). Putting the unmanned aerial vehicle into a distance difference space model, and if the position falls on a correction point, directly calculating the correction position of the non-cooperative unmanned aerial vehicle according to the current 3-dimensional distance difference value of the correction point
Figure RE-GDA0003754407570000053
If the position is located at the non-correction point, taking the 3-dimensional distance difference value of 4 correction points of the grid where the position is located, calculating the distance difference of the position according to the formulas (4) - (6), and obtaining the system static correction position of the position
Figure RE-GDA0003754407570000054
And releasing the unmanned aerial vehicle of the owner to fly together according to the static correction position of the system, returning the accurate GPS position of the unmanned aerial vehicle of the owner when the unmanned aerial vehicle of the owner approaches to the non-cooperative unmanned aerial vehicle, calculating the distance difference between the accurate position of the unmanned aerial vehicle of the owner and the static correction position of the system, taking the distance difference as the distance difference of the non-cooperative unmanned aerial vehicle, and correcting the accurate position of the non-cooperative unmanned aerial vehicle in real time. In the accompanying flight process, the unmanned aerial vehicle of one party is close to the non-cooperative unmanned aerial vehicle for many times, and each intersection point is used as an assimilation point, so that the non-cooperative unmanned aerial vehicle can be continuously updated and positioned in real time. A flight sequence sample set is constructed with the collected self-flight data and non-cooperative drone flight data, each sample being represented as (TDOA location, precise location). Constructing a GRU sequence prediction model, taking unmanned aerial vehicle self-flying sequence samples carrying soft modules of one party as a training set, training the GRU sequence prediction model, taking a flying sequence of a non-cooperative unmanned aerial vehicle as a prediction set, and taking the GRU modelAnd performing decision-making level fusion on the prediction result and the assimilation positioning result corrected in real time to obtain the accurate coordinate of final positioning.

Claims (5)

1. A non-cooperative unmanned aerial vehicle accurate positioning method based on differential correction comprises the following steps:
A. and constructing a distance difference space model. Setting a distributed time difference positioning space range, setting a coordinate point, called a correction point, in each direction at an interval of 1m in a space coordinate system, marking the position coordinates of the coordinate points by using accurate longitude and latitude and height, and forming a space grid by all the correction points. Because of the difference of space environment and the interference of various signals, the coordinate of the unmanned aerial vehicle given by the TDOA positioning system has different errors at each position, 3 distance difference dimensions are added for each correction point to form 6-dimensional position coordinates, and the position coordinate of the ith correction point is
Figure FDA0003688541220000011
The distance difference model is used for storing accurate 3-dimensional coordinates and 3-dimensional difference data of calculated correction points, and all 6-dimensional coordinate points at intervals of 1m in a correction space form a distance difference space model.
B. A differential-based systematic spatial model location correction. The unmanned aerial vehicle carrying the soft module in one part is released to fly automatically in the defense space, the GPS accurate position of the unmanned aerial vehicle is returned in the flying process, and the flying track covers each grid of the distance difference space model through multiple rounds of self-flying. Aiming at each correction point in the space model, acquiring a plurality of accurate positions returned in 4 grids around the correction point and TDOA coordinates corresponding to each position, and respectively marking as P 1 ，...，P i ，...，P n And P' 1 ，...，P′ i ，...，P′ n In which P is i Is marked as an accurate position
Figure FDA0003688541220000012
Position P 'of TDOA system location' i Is recorded as (x' i ，y′ i ，z′ i ). Computing a grid based on the precise location and TDOA system coordinates according to equations (1) - (3)The 3-dimensional distance difference of the middle positioning point is respectively marked as d x ，d y ，d z 。
Figure FDA0003688541220000013
Figure FDA0003688541220000014
Figure FDA0003688541220000015
D of each correction point is obtained according to calculation x ，d y ，d z And updating the distance difference value of each correction point in the distance difference space model to realize systematic positioning correction of the whole space model.
C. Non-cooperative unmanned aerial vehicle accurate positioning based on real-time correction. When the TDOA system detects the signal of the invading unmanned aerial vehicle, the real-time TDOA position of the invading unmanned aerial vehicle is calculated and taken as the initial position P 0 (x′ 0 ，y′ 0 ，z′ 0 ). Putting the unmanned aerial vehicle into a distance difference space model, and if the position falls on a correction point, directly calculating the correction position of the non-cooperative unmanned aerial vehicle according to the current 3-dimensional distance difference value of the correction point
Figure FDA0003688541220000016
If the position is located at the non-correction point, taking the 3-dimensional distance difference value of 4 correction points of the grid where the position is located, calculating the distance difference of the position according to the formulas (4) - (6), and obtaining the system static correction position of the position
Figure FDA0003688541220000017
Figure FDA0003688541220000018
Figure FDA0003688541220000019
Figure FDA0003688541220000021
And releasing the unmanned aerial vehicle of the owner to fly together according to the static correction position of the system, returning the self accurate GPS position by the unmanned aerial vehicle of the owner when the unmanned aerial vehicle is close to the non-cooperative unmanned aerial vehicle (defined as a cross point within the range of 30 cm), calculating the distance difference between the accurate position of the unmanned aerial vehicle of the owner and the static correction position of the system, taking the distance difference as the distance difference of the non-cooperative unmanned aerial vehicle, and correcting the accurate position of the non-cooperative unmanned aerial vehicle in real time. In the accompanying flight process, the unmanned aerial vehicle of one party is close to the non-cooperative unmanned aerial vehicle for many times, and each intersection point is used as an assimilation point, so that the non-cooperative unmanned aerial vehicle can be continuously updated and positioned in real time. A flight sequence sample set is constructed with the collected self-flight data and non-cooperative drone flight data, each sample being represented as (TDOA location, precise location). And (3) constructing a GRU sequence prediction model, taking an unmanned aerial vehicle self-flying sequence sample carrying a soft module in one party as a training set, training the GRU sequence prediction model, taking a flying sequence of a non-cooperative unmanned aerial vehicle as a prediction set, and performing decision-level fusion on a prediction result of the GRU model and an assimilation positioning result corrected in real time to obtain accurate coordinates of final positioning.
2. The method as claimed in claim 1, wherein in step a, the TDOA is a method of using time difference of arrival to perform positioning. The distance of the signal source is determined by measuring the time of arrival of the signal at the monitoring station.
3. The method for accurately positioning a non-cooperative drone based on differential correction as claimed in claim 1, wherein in step B, the soft module is firmware programming code for embedding identity information of the drone.
4. The method as claimed in claim 1, wherein in step C, the GRU is a neural network, the concept of reset gate and refresh gate is introduced, the gate control mechanism is used to control and manage the information flow between cells in the neural network, and the past information is memorized while some unimportant information is selectively forgotten, so as to solve the problem of gradient in long-term memory and back propagation.
5. The invention provides a differential correction-based non-cooperative unmanned aerial vehicle accurate positioning device, which comprises the following modules:
the distance difference space model construction module comprises: setting a distributed time difference positioning space range, setting a coordinate point, called a correction point, in each direction at an interval of 1m in a space coordinate system, marking the position coordinates of the coordinate points by using accurate longitude and latitude and height, and forming a space grid by all the correction points. Adding 3 distance difference dimensions for each correction point to form 6-dimensional position coordinates, wherein the position coordinate of the ith correction point is
Figure FDA0003688541220000022
The distance difference model is used for storing accurate 3-dimensional coordinates and 3-dimensional difference data of calculated correction points, and all 6-dimensional coordinate points at intervals of 1m in a correction space form a distance difference space model.
The space model positioning correction module: aiming at each correction point in the space model, acquiring a plurality of accurate positions of self-flying return of the unmanned aerial vehicle in 4 grids around the correction point and TDOA coordinates corresponding to each position, and respectively recording as P 1 ，...，P i ，...，P n And P' 1 ，...，P′ i ，...，P′ n In which P is i Is marked as an accurate position
Figure FDA0003688541220000023
Location P 'of TDOA System location' i Is recorded as (x' i ，y′ i ，z′ i ). Calculating the 3-dimensional distance difference of the middle positioning points of the grid according to the formulas (1) to (3), and respectively recording the 3-dimensional distance difference as d x ，d y ，d z . D of each correction point is obtained according to calculation x ，d y ，d z And updating the distance difference value of each correction point in the distance difference space model to realize systematic positioning correction of the whole space model.
Non-cooperative unmanned aerial vehicle accurate positioning module: when the TDOA system detects the signal of the invading unmanned aerial vehicle, the real-time TDOA position of the invading unmanned aerial vehicle is calculated and taken as the initial position P 0 (x′ 0 ，y′ 0 ，z′ 0 ). Putting the unmanned aerial vehicle into a distance difference space model, and if the position falls on a correction point, directly calculating the correction position of the non-cooperative unmanned aerial vehicle according to the current 3-dimensional distance difference value of the correction point
Figure FDA0003688541220000031
If the position is located at the non-correction point, taking the 3-dimensional distance difference value of 4 correction points of the grid where the position is located, calculating the distance difference of the position according to the formulas (4) - (6), and obtaining the system static correction position of the position
Figure FDA0003688541220000032
And releasing the unmanned aerial vehicle of the owner to fly together according to the static correction position of the system, returning the self accurate GPS position by the unmanned aerial vehicle of the owner when the unmanned aerial vehicle is close to the non-cooperative unmanned aerial vehicle (defined as a cross point within the range of 30 cm), calculating the distance difference between the accurate position of the unmanned aerial vehicle of the owner and the static correction position of the system, taking the distance difference as the distance difference of the non-cooperative unmanned aerial vehicle, and correcting the accurate position of the non-cooperative unmanned aerial vehicle in real time. In the accompanying flight process, the unmanned aerial vehicle of one party is close to the non-cooperative unmanned aerial vehicle for many times, and each intersection point is used as an assimilation point, so that the non-cooperative unmanned aerial vehicle can be continuously updated and positioned in real time. A flight sequence sample set is constructed with the collected self-flight data and non-cooperative drone flight data, each sample being represented as (TDOA location, precise location). Constructing a GRU sequence prediction model, and training GRU sequence prediction by using unmanned aerial vehicle self-flying sequence samples carrying soft modules of one party as a training setAnd the model takes the flight sequence of the non-cooperative unmanned aerial vehicle as a prediction set, and carries out decision-making fusion on the prediction result of the GRU model and the assimilation positioning result corrected in real time to obtain the accurate coordinate of final positioning.
CN202210654153.2A 2022-06-10 2022-06-10 Differential correction-based non-cooperative unmanned aerial vehicle accurate positioning method and device Pending CN115079089A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116561530A (en) * 2023-05-26 2023-08-08 深圳大漠大智控技术有限公司 Unmanned aerial vehicle flight data analysis method, device, equipment and medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116561530A (en) * 2023-05-26 2023-08-08 深圳大漠大智控技术有限公司 Unmanned aerial vehicle flight data analysis method, device, equipment and medium
CN116561530B (en) * 2023-05-26 2024-01-26 深圳大漠大智控技术有限公司 Unmanned aerial vehicle flight data analysis method, device, equipment and medium

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