CN113498020A - Unmanned aerial vehicle cluster belief propagation cooperative positioning method - Google Patents
Unmanned aerial vehicle cluster belief propagation cooperative positioning method Download PDFInfo
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- CN113498020A CN113498020A CN202110766566.5A CN202110766566A CN113498020A CN 113498020 A CN113498020 A CN 113498020A CN 202110766566 A CN202110766566 A CN 202110766566A CN 113498020 A CN113498020 A CN 113498020A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
- G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
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- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention discloses an unmanned aerial vehicle cluster belief propagation cooperative positioning method, which comprises the steps of acquiring GPS positioning coordinate data of all unmanned aerial vehicles; recording and labeling coordinates of all unmanned aerial vehicles; the self information of the unmanned aerial vehicle and the ranging information between the monitoring station and the monitoring station are transmitted through network signals; testing the distance between every two unmanned planes in the unmanned plane cluster by methods such as signal arrival time or received signal strength and the like, and sending the measured distance information to a monitoring station; the relative coordinates of all unmanned aerial vehicles are transformed into the positioning coordinates of the GPS by the least square principle to obtain the absolute coordinates of all unmanned aerial vehicles in the unmanned aerial vehicle cluster, and the absolute coordinates are sent to the whole unmanned aerial vehicle cluster.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle cluster belief propagation cooperative positioning method.
Background
An unmanned aircraft, abbreviated as "drone", and abbreviated in english as "UAV", is an unmanned aircraft that is operated by a radio remote control device and a self-contained program control device, or is operated autonomously, either completely or intermittently, by an onboard computer.
In recent years, the unmanned aerial vehicle cluster cooperation technology is increasingly concerned at home and abroad. The unmanned aerial vehicle cluster has the advantages of large working range, high reliability, capability of simultaneously executing multiple tasks, high overall efficiency and the like, and can be used in the fields of disaster exploration, rescue and the like. The unmanned aerial vehicle cluster technology, namely an organization mode of certain formation arrangement and task allocation of a plurality of unmanned aerial vehicles for adapting to task requirements, comprises formation generation, maintenance and change of cluster flight, and planning and organization of cluster flight tasks, and is an important trend of future unmanned aerial vehicle flight technology development.
Disclosure of Invention
Technical problem to be solved
In order to overcome the defects in the prior art, a belief propagation cooperative positioning method for an unmanned aerial vehicle cluster is provided so as to solve the problems provided in the background art.
(II) technical scheme
The invention is realized by the following technical scheme: the invention provides an unmanned aerial vehicle cluster belief propagation cooperative positioning method, which is characterized by comprising the following steps: the method comprises the following steps:
s1: acquiring GPS positioning coordinate data of all unmanned aerial vehicles;
s2: recording and labeling coordinates of all unmanned aerial vehicles;
s3: the self information of the unmanned aerial vehicle and the ranging information between the monitoring station and the monitoring station are transmitted through network signals;
s4: testing the distance between every two unmanned planes in the unmanned plane cluster by methods such as signal arrival time or received signal strength and the like, and sending the measured distance information to a monitoring station;
s5: and transforming the relative coordinates of all the unmanned aerial vehicles into positioning coordinates of a GPS (global positioning system) by a least square principle to obtain absolute coordinates of all the unmanned aerial vehicles in the unmanned aerial vehicle cluster, and transmitting the absolute coordinates to the whole unmanned aerial vehicle cluster.
Further, the unmanned aerial vehicle cluster is composed of a reference unmanned aerial vehicle and an unmanned aerial vehicle to be positioned.
In step 2, G is { gi }, gi is the GPS positioning coordinates of the ith drone, i is 1,2, …, N, and N is the number of drones.
In step 4, dij is the distance between the ith drone and the jth drone, and i, j is 1,2, …, N.
Further, in step 4, the central unmanned aerial vehicle constructs the received distance information into a distance matrix, and an improved multidimensional scale analysis algorithm is adopted according to the distance matrix.
Further, in step 5, the central drone transforms the relative coordinates of all drones into the positioning coordinates of the GPS by using the least square principle to obtain the absolute coordinates of all drones in the drone swarm, and sends the absolute coordinates to the whole drone swarm.
(III) advantageous effects
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an unmanned aerial vehicle cluster belief propagation cooperative positioning method, which obtains a distance matrix by testing the distance between every two unmanned aerial vehicles in an unmanned aerial vehicle cluster, obtains the relative coordinates of all unmanned aerial vehicles by adopting an improved multidimensional scale analysis algorithm on the distance matrix, realizes the cooperative positioning of the unmanned aerial vehicle cluster, and has simple hardware realization and insensitive positioning precision to distance measurement errors.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides an unmanned aerial vehicle cluster belief propagation cooperative positioning method, which is characterized by comprising the following steps: the method comprises the following steps:
s1: acquiring GPS positioning coordinate data of all unmanned aerial vehicles;
s2: recording and labeling coordinates of all unmanned aerial vehicles;
s3: the self information of the unmanned aerial vehicle and the ranging information between the monitoring station and the monitoring station are transmitted through network signals;
s4: testing the distance between every two unmanned planes in the unmanned plane cluster by methods such as signal arrival time or received signal strength and the like, and sending the measured distance information to a monitoring station;
s5: and transforming the relative coordinates of all the unmanned aerial vehicles into positioning coordinates of a GPS (global positioning system) by a least square principle to obtain absolute coordinates of all the unmanned aerial vehicles in the unmanned aerial vehicle cluster, and transmitting the absolute coordinates to the whole unmanned aerial vehicle cluster.
Further, the unmanned aerial vehicle cluster is composed of a reference unmanned aerial vehicle and an unmanned aerial vehicle to be positioned.
In step 2, G is { gi }, gi is the GPS positioning coordinates of the ith drone, i is 1,2, …, N, and N is the number of drones.
In step 4, dij is the distance between the ith drone and the jth drone, and i, j is 1,2, …, N.
Further, in step 4, the central unmanned aerial vehicle constructs the received distance information into a distance matrix, and an improved multidimensional scale analysis algorithm is adopted according to the distance matrix.
Further, in step 5, the central drone transforms the relative coordinates of all drones into the positioning coordinates of the GPS by using the least square principle to obtain the absolute coordinates of all drones in the drone swarm, and sends the absolute coordinates to the whole drone swarm.
The invention provides an unmanned aerial vehicle cluster belief propagation cooperative positioning method, which obtains a distance matrix by testing the distance between every two unmanned aerial vehicles in an unmanned aerial vehicle cluster, obtains the relative coordinates of all unmanned aerial vehicles by adopting an improved multidimensional scale analysis algorithm on the distance matrix, realizes the cooperative positioning of the unmanned aerial vehicle cluster, and has simple hardware realization and insensitive positioning precision to distance measurement errors.
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention and do not limit the spirit and scope of the present invention. Various modifications and improvements of the technical solutions of the present invention may be made by those skilled in the art without departing from the design concept of the present invention, and the technical contents of the present invention are all described in the claims.
Claims (6)
1. An unmanned aerial vehicle cluster belief propagation cooperative positioning method is characterized by comprising the following steps: the method comprises the following steps:
s1: acquiring GPS positioning coordinate data of all unmanned aerial vehicles;
s2: recording and labeling coordinates of all unmanned aerial vehicles;
s3: the self information of the unmanned aerial vehicle and the ranging information between the monitoring station and the monitoring station are transmitted through network signals;
s4: testing the distance between every two unmanned planes in the unmanned plane cluster by methods such as signal arrival time or received signal strength and the like, and sending the measured distance information to a monitoring station;
s5: and transforming the relative coordinates of all the unmanned aerial vehicles into positioning coordinates of a GPS (global positioning system) by a least square principle to obtain absolute coordinates of all the unmanned aerial vehicles in the unmanned aerial vehicle cluster, and transmitting the absolute coordinates to the whole unmanned aerial vehicle cluster.
2. The unmanned aerial vehicle cluster belief propagation co-location method of claim 1, characterized in that: the unmanned aerial vehicle cluster is composed of a reference unmanned aerial vehicle and an unmanned aerial vehicle to be positioned.
3. The unmanned aerial vehicle cluster belief propagation co-location method of claim 2, characterized in that: in step 2, G is { gi }, gi is a GPS positioning coordinate of the ith drone, i is 1,2, …, and N is the number of drones.
4. The unmanned aerial vehicle cluster belief propagation co-location method of claim 3, characterized in that: in step 4, dij is the distance between the ith drone and the jth drone, and i, j is 1,2, …, N.
5. The unmanned aerial vehicle cluster belief propagation co-location method of claim 4, characterized in that: and 4, constructing the received distance information into a distance matrix by the central unmanned aerial vehicle, and adopting an improved multi-dimensional analysis algorithm according to the distance matrix.
6. The unmanned aerial vehicle cluster belief propagation co-location method of claim 5, characterized in that: in step 5, the central unmanned aerial vehicle transforms the relative coordinates of all unmanned aerial vehicles into the positioning coordinates of the GPS by adopting a least square principle to obtain the absolute coordinates of all unmanned aerial vehicles in the unmanned aerial vehicle cluster, and sends the absolute coordinates to the whole unmanned aerial vehicle cluster.
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| CN202110766566.5A CN113498020A (en) | 2021-07-07 | 2021-07-07 | Unmanned aerial vehicle cluster belief propagation cooperative positioning method |
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| CN202110766566.5A CN113498020A (en) | 2021-07-07 | 2021-07-07 | Unmanned aerial vehicle cluster belief propagation cooperative positioning method |
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| CN111123341A (en) * | 2019-11-15 | 2020-05-08 | 西安电子科技大学 | Three-dimensional co-location method for unmanned aerial vehicle group |
| CN111918389A (en) * | 2020-08-25 | 2020-11-10 | 成都飞英思特科技有限公司 | Outdoor positioning method and device based on unmanned aerial vehicle gateway |
| CN112584308A (en) * | 2020-12-09 | 2021-03-30 | 中国电子科技集团公司第二十研究所 | Unmanned aerial vehicle cluster over-the-horizon networking device and method based on Beidou system |
| CN112731500A (en) * | 2020-12-30 | 2021-04-30 | 西安电子科技大学 | Method for three-dimensional positioning of outdoor unmanned aerial vehicle and indoor unmanned aerial vehicle |
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2021
- 2021-07-07 CN CN202110766566.5A patent/CN113498020A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160080951A1 (en) * | 2013-05-07 | 2016-03-17 | Telefonaktiebolaget L M Ericsson (Publ) | Communications Links Assessment |
| US20160337027A1 (en) * | 2015-05-13 | 2016-11-17 | Ubiqomm Llc | Ground terminal and gateway beam pointing toward an unmanned aerial vehicle (uav) for network access |
| CN111123341A (en) * | 2019-11-15 | 2020-05-08 | 西安电子科技大学 | Three-dimensional co-location method for unmanned aerial vehicle group |
| CN111918389A (en) * | 2020-08-25 | 2020-11-10 | 成都飞英思特科技有限公司 | Outdoor positioning method and device based on unmanned aerial vehicle gateway |
| CN112584308A (en) * | 2020-12-09 | 2021-03-30 | 中国电子科技集团公司第二十研究所 | Unmanned aerial vehicle cluster over-the-horizon networking device and method based on Beidou system |
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