A forest guiding positioning method based on a spatial configuration candidate of a UAV
By using an air-ground cooperative positioning method that integrates UWB base stations and personnel tags on drones, combined with spatial configuration and RANSAC algorithm, the positioning accuracy problem caused by satellite signal obstruction in dense forest environments was solved, achieving high-precision personnel positioning in forest areas.
Patent Information
- Application Number
- CN202610690404.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-19
- Publication Date
- 2026-08-25
AI Technical Summary
In dense forest environments, satellite navigation signals are blocked by the tree canopy, resulting in reduced positioning accuracy. Existing UAV guidance methods are difficult to operate and their accuracy depends on the deployment of base stations, and there is a lack of effective candidate methods for spatial configuration.
By using UWB base stations carried by drones and UWB tags carried by personnel, high-precision positioning of personnel in forest areas is achieved through spatial configuration constraints and RANSAC iterative models, combined with least squares method solution.
It improves positioning accuracy and operational feasibility in dense forest environments and provides convenient location information support.
Smart Images
Figure CN122640833A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a forest area guidance and positioning method based on candidate spatial configurations of unmanned aerial vehicles (UAVs), belonging to the field of navigation, positioning and information fusion application technology. Background Technology
[0002] High-precision navigation and positioning are crucial for ensuring the safety of firefighters, forest rangers, and other personnel in forest areas. The unique characteristics of dense forest environments mean that navigation signals are weakened and interfered with by leaves and tree trunks after passing through the canopy, leading to multipath interference and directly impacting the positioning accuracy of existing GNSS receivers in forest environments. Therefore, positioning in dense forest environments remains a long-standing challenge. Currently, using unmanned aerial vehicles (UAVs) for aerial guidance of personnel working in the forest is an effective method. Research shows that the highly penetrating UWB positioning method can achieve a certain level of ranging accuracy in dense forest environments. By using UAVs to achieve air-ground collaborative positioning, it can be used for personnel positioning and forest area surveying.
[0003] Although UWB positioning technology has achieved certain results in dense forest environments, the optimization of positioning results in practical applications still depends on the deployment density and calibration of UWB base stations. While rendezvous positioning guided by UAVs provides a solution for non-calibrated mobile base stations, UAV flight also presents practical operational difficulties, and positioning accuracy depends on spatial configuration. There is an urgent need to conduct research on forest area guidance and positioning methods based on UAV spatial configuration candidates, but there are no relevant applications in the existing technology. Summary of the Invention
[0004] In view of this, the present invention proposes a forest area guidance and positioning method based on UAV spatial configuration candidate. This method utilizes a UAV-equipped UWB-based air-ground collaborative positioning method in forest areas. Through spatial configuration constraints, it improves the positioning accuracy of UAV-equipped UWB in forest areas and enhances the feasibility of practical applications.
[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:
[0006] A forest area guidance and positioning method based on UAV spatial configuration candidates includes the following steps:
[0007] (1) Establish a UWB-guided personnel positioning system for unmanned aerial vehicles (UAVs) in forest areas, including UAVs and personnel entering the forest area. The UAVs are equipped with satellite navigation and UWB base stations. The UAVs fly around the personnel in the forest area while maintaining a consistent flight altitude. Personnel entering the forest area are equipped with satellite navigation and UWB tags.
[0008] (2) Based on the process of personnel entering the forest area conducting two-way ranging and communication with UWB base stations of UAVs through UWB tags, an analytical equation is established;
[0009] (3) Obtain N initial candidate points for UAVs through spatial sequence configuration constraints; where N > 4;
[0010] (4) Based on RANSAC, the initial candidate points are screened twice. The candidate points after the second screening are substituted into the analytical equation and the location of the people entering the forest area is obtained by the least squares method.
[0011] Furthermore, the specific process of step (2) is as follows:
[0012] Define the position of a person stationary when entering the forest area as The UWB base station for drones obtains information via satellite navigation. The coordinates of the time are Based on the process of two-way ranging and communication between personnel entering the forest area and UWB base stations of UAVs via UWB tags, the following analytical equation is established:
[0013]
[0014]
[0015]
[0016]
[0017] In the formula, for Real-time drone location for The distance measured between personnel and UWB base stations of drones at any given time; for Real-time drone location for Distance measurement between personnel in dense forests and UWB base stations for drones. for Real-time drone location for The distance between personnel in dense forests and UWB base stations for drones is measured at all times.
[0018] Furthermore, the specific process of step (3) is as follows:
[0019] Select the initial point coordinates of the UAV as Based on the initial spatial configuration candidate method, the UAV trajectory is traversed through time series analysis, and N points are selected as initial candidate points. Then, the... Initial candidate point coordinates Satisfy the following equation:
[0020]
[0021] in, This represents the maximum angle range that the UAV can select starting from its initial position coordinates. satisfy .
[0022] Furthermore, the specific process of step (4) is as follows:
[0023] An N-to-M method is used to construct an iterative RANSAC model to filter initial candidate points. And define the threshold. The loss function is defined as the sum of the vertical errors between the obtained location coordinates of personnel entering the forest area and the candidate locations of the UAV. The iteration terminates when the total error is less than a threshold. ;
[0024] The iterative process is as follows:
[0025] The first step is to randomly select M initial candidate points and solve the analytical equations using the least squares method to obtain the location coordinates of personnel entering the forest area. ;
[0026] The second step is to calculate the error of the loss function:
[0027]
[0028] The third step is to determine whether the iteration termination condition is met. If the result is correct, the iteration ends, and the candidate point location results and the location results of people entering the forest area are output; otherwise, the error is recorded and the process returns to step one.
[0029] The beneficial effects achieved by this invention compared with the prior art are as follows:
[0030] 1. This invention utilizes a drone-guided positioning system composed of drones and personnel entering dense forests. It leverages the strong penetration of UWB to transmit the absolute position of personnel in dense forest environments and improves the practical usability of the drone-guided positioning scheme by constructing candidate coordinates in space.
[0031] 2. This invention can achieve accurate positioning in dense forest environments.
[0032] 3. The method of the present invention is simple and easy to implement, and can provide location information assurance for workers operating under the forest canopy. Attached Figure Description
[0033] Figure 1 A schematic diagram illustrating the principle of the method of this invention. Detailed Implementation
[0034] To better illustrate the purpose and advantages of the present invention, the technical solution of the present invention will be further described below.
[0035] A forest area guidance and positioning method based on UAV spatial configuration candidate analysis is proposed. This method utilizes a forest area guidance and positioning system composed of a UAV and personnel entering the forest area. The UAV is equipped with satellite navigation and a UWB base station, and flies around the personnel entering the forest area. Distance measurement is achieved through the UWB base station and the UWB tags of the personnel entering the forest area. Figure 1 This invention rapidly obtains coarse candidate coordinates of UWB base stations through spatial configuration, and then performs secondary fine-tuning of these candidate coordinates based on RANSAC and least squares methods, achieving more accurate location analysis of personnel in forest environments. The method is simple and easy to implement, providing location information assurance for personnel in mountainous and dense forest environments.
[0036] The method specifically includes the following steps:
[0037] (1) Establish a UWB-guided personnel positioning system for unmanned aerial vehicles (UAVs) in forest areas, including UAVs and personnel entering the forest area. The UAVs are equipped with satellite navigation and UWB base stations. The UAVs fly around the personnel in the forest area while maintaining a consistent flight altitude. Personnel entering the forest area are equipped with satellite navigation and UWB tags.
[0038] (2) Based on the process of personnel entering the forest area conducting two-way ranging and communication with the UWB base station of the UAV through UWB tags, an analytical equation is established; specific implementation method:
[0039] Define the position of a person stationary when entering the forest area as The UWB base station for drones obtains information via satellite navigation. The coordinates of the time are Based on the process of two-way ranging and communication between personnel entering the forest area and UWB base stations of UAVs via UWB tags, the following analytical equation is established:
[0040]
[0041]
[0042]
[0043]
[0044] In the formula, for Real-time drone location for The distance measured between personnel and UWB base stations of drones at any given time; for Real-time drone location for Distance measurement between personnel in dense forests and UWB base stations for drones. for Real-time drone location for The distance between personnel in dense forests and UWB base stations for drones is measured at all times.
[0045] (3) Obtain N initial candidate points for UAVs through spatial sequence configuration constraints; where N>4; specific implementation method:
[0046] Select the initial point coordinates of the UAV as According to the initial spatial configuration candidate method, the UAV trajectory is traversed through time series analysis to select N points as initial candidate points. In this embodiment, N is 8. Figure 1 middle Then the first Initial candidate point coordinates Satisfy the following equation:
[0047]
[0048] in, This represents the maximum angle range that the UAV can select starting from its initial position coordinates. satisfy .
[0049] (4) Based on RANSAC, a secondary screening of initial candidate points is performed. The candidate points after secondary screening are substituted into the analytical equation, and the location of people entering the forest area is obtained by solving the least squares method. Specific implementation method:
[0050] An N-to-M method is used to construct an iterative RANSAC model to filter initial candidate points. And define the threshold. The loss function is defined as the sum of the vertical errors between the obtained location coordinates of personnel entering the forest area and the candidate locations of the UAV. The iteration terminates when the total error is less than a threshold. This embodiment can use an 8-out-of-6 selection method, that is... and define ;
[0051] The iterative process is as follows:
[0052] The first step is to randomly select M initial candidate points and solve the analytical equations using the least squares method to obtain the location coordinates of personnel entering the forest area. ;
[0053] The second step is to calculate the error of the loss function:
[0054]
[0055] The third step is to determine whether the iteration termination condition is met. If the result is correct, the iteration ends, and the candidate point location results and the location results of people entering the forest area are output; otherwise, the error is recorded and the process returns to step one.
Claims
1. A forest area guidance and positioning method based on UAV spatial configuration candidates, characterized in that, Includes the following steps: (1) Establish a UWB-guided personnel positioning system for unmanned aerial vehicles (UAVs) in forest areas, including UAVs and personnel entering the forest area. The UAVs are equipped with satellite navigation and UWB base stations. The UAVs fly around the personnel in the forest area while maintaining a consistent flight altitude. Personnel entering the forest area are equipped with satellite navigation and UWB tags. (2) Based on the process of personnel entering the forest area conducting two-way ranging and communication with UWB base stations of UAVs through UWB tags, an analytical equation is established; (3) Obtain N initial candidate points for UAVs through spatial sequence configuration constraints; where N > 4; (4) Based on RANSAC, the initial candidate points are screened twice. The candidate points after the second screening are substituted into the analytical equation and the location of the people entering the forest area is obtained by the least squares method.
2. The forest area guidance and positioning method based on RANSAC-based UAV spatial configuration candidate as described in claim 1, characterized in that, The specific process of step (2) is as follows: Define the position of a person stationary when entering the forest area as The UWB base station for drones obtains information via satellite navigation. The coordinates of the time are Based on the process of two-way ranging and communication between personnel entering the forest area and UWB base stations of UAVs via UWB tags, the following analytical equation is established: In the formula, for Real-time drone location for The distance measured between personnel and UWB base stations of drones at any given time; for Real-time drone location for Distance measurement between personnel in dense forests and UWB base stations for drones. for Real-time drone location for The distance between personnel in dense forests and UWB base stations for drones is measured at all times.
3. The forest area guidance and positioning method based on UAV spatial configuration candidates according to claim 2, characterized in that, The specific process of step (3) is as follows: Select the initial point coordinates of the UAV as Based on the initial spatial configuration candidate method, the UAV trajectory is traversed through time series analysis, and N points are selected as initial candidate points. Then, the... Initial candidate point coordinates Satisfy the following equation: in, This represents the maximum angle range that the UAV can select starting from its initial position coordinates. satisfy .
4. The forest area guidance and positioning method based on UAV spatial configuration candidates according to claim 3, characterized in that, The specific process of step (4) is as follows: An N-to-M method is used to construct an iterative RANSAC model to filter initial candidate points. And define the threshold. The loss function is defined as the sum of the vertical errors between the obtained location coordinates of personnel entering the forest area and the candidate locations of the UAV. The iteration terminates when the total error is less than a threshold. ; The iterative process is as follows: The first step is to randomly select M initial candidate points and solve the analytical equations using the least squares method to obtain the location coordinates of personnel entering the forest area. ; The second step is to calculate the error of the loss function: The third step is to determine whether the iteration termination condition is met. If the result is correct, the iteration ends, and the candidate point location results and the location results of people entering the forest area are output; otherwise, the error is recorded and the process returns to step one.