CN-121720534-B - Adaptive configuration method and system for traffic geological disaster unmanned aerial vehicle sensor

CN121720534BCN 121720534 BCN121720534 BCN 121720534BCN-121720534-B

Abstract

The invention relates to the technical field of geological disaster monitoring and discloses a self-adaptive configuration method and a self-adaptive configuration system for a traffic geological disaster unmanned aerial vehicle sensor. The method comprises the steps of obtaining disaster characteristics and environmental parameters of a target area, quantifying sensor capacity, establishing an adaptation measurement matrix between the disaster characteristics and the sensor capacity, generating a sensor working parameter configuration scheme, and controlling an unmanned aerial vehicle to monitor and collect data so as to optimize the weight coefficient of the adaptation measurement matrix. The invention can adaptively adjust the sensor configuration according to disaster characteristics and environmental conditions, improves the monitoring precision and efficiency, and reduces the monitoring cost.

Inventors

ZHANG JUNFENG
WANG LITAO
CHEN XIAOWEI
WANG FUTAO
LU PENG
WANG ZHENQING

Assignees

北京捷翔天地信息技术有限公司
中国科学院空天信息创新研究院

Dates

Publication Date: 20260508
Application Date: 20260206

Claims (8)

1. The adaptive configuration method of the traffic geological disaster unmanned aerial vehicle sensor is characterized by comprising the following steps of: obtaining geological disaster type characteristics and environmental dynamic parameters of a target monitoring area; based on a preset sensor performance constraint rule and detection capability mapping relation, performing capability quantitative characterization on multiple types of sensors carried by the unmanned aerial vehicle to obtain a sensor capability vector set; Processing each capability vector in the sensor capability vector set according to the geological disaster type features, establishing a quantized adaptation relation between disaster feature dimensions and sensor capability dimensions, and obtaining an adaptation metric matrix, wherein the method comprises the following steps: Extracting disaster space distribution form information and disaster evolution stage identification information from the geological disaster type features, converting the disaster space distribution form information into space scale feature dimensions and space complexity feature dimensions, and converting the disaster evolution stage identification information into time evolution rate feature dimensions and stability feature dimensions to obtain a disaster feature dimension set; Extracting a detection range function, a resolution function and a data acquisition rate function carried by each capability vector from the sensor capability vector set; Mapping the detection range function into a space coverage capability dimension, mapping the resolution function into a detail recognition capability dimension, and mapping the data acquisition rate function into a time sequence tracking capability dimension to obtain a sensor capability dimension set; Determining a matching rule between the disaster feature dimension set and the sensor capability dimension set, and according to the matching rule, performing correlation strength calculation on each feature dimension in the disaster feature dimension set and each capability dimension in the sensor capability dimension set to generate an adaptation metric matrix, wherein each element in the adaptation metric matrix represents the dependence degree of a specific disaster feature dimension on a specific sensor capability dimension; According to the adaptive measurement matrix and the environment dynamic parameter, performing collaborative solution by coupling multi-dimensional constraint, and generating a sensor working parameter configuration scheme, which comprises the following steps: Determining disaster monitoring requirement constraint according to the adaptation metric values corresponding to each disaster characteristic dimension in the adaptation metric matrix; Determining an allowable adjustment range of the working parameters of the sensor according to the environmental factors influencing the working state of the sensor in the environmental dynamic parameters to obtain environmental adaptability constraint; Combining the disaster monitoring demand constraint and the environment adaptability constraint to form a multi-dimensional constraint set; determining a constraint coupling relation expression aiming at the multi-dimensional constraint set, and determining a mapping function between a sensor working parameter and the multi-dimensional constraint set through the constraint coupling relation expression; In a feasible domain defined by the mapping function, performing optimization calculation on the adaptation metric values in the adaptation metric matrix, and determining a sensor working parameter combination for enabling the adaptation metric values to reach a target state; The sensor working parameter combination is converted into working mode setting parameters and data acquisition control parameters of each sensor, and a sensor working parameter configuration scheme is obtained; And controlling the working state of each sensor of the unmanned aerial vehicle based on the sensor working parameter configuration scheme, driving the unmanned aerial vehicle to execute monitoring tasks along a preset route and collecting geological disaster detection data, wherein the geological disaster detection data are used for optimally adjusting the weight coefficient of the corresponding disaster characteristic dimension in the adaptive measurement matrix.
2. The method of claim 1, wherein performing the capability-based characterization on the multi-type sensor carried by the unmanned aerial vehicle based on the preset sensor performance constraint rule and the detection capability mapping relation to obtain the sensor capability vector set comprises: Extracting physical characteristic parameters of each sensor from multiple types of sensors carried by the unmanned aerial vehicle; Based on a preset sensor performance constraint rule, determining a mapping function relation between physical characteristic parameters and capacity characterization quantities, and carrying out dimension unified processing on the physical characteristic parameters to obtain standardized values; Substituting the standardized numerical value into a corresponding conversion rule according to the mapping function relation to generate a detection range function, a resolution function and a data acquisition rate function as capacity characterization quantities; dividing the multi-type sensor into different capability categories according to the positions of the effective detection distance boundary and the angular resolution boundary in the physical characteristic parameters in a preset dividing threshold; And carrying out association combination on the capacity characterization quantity and the capacity category to construct a sensor capacity vector set.
3. The method of claim 1, wherein converting the disaster spatial distribution morphology information into a spatial scale feature dimension and a spatial complexity feature dimension, and converting the disaster evolution stage identification information into a time evolution rate feature dimension and a stability feature dimension, to obtain a disaster feature dimension set, comprises: determining a mapping rule of a geometric boundary and a spatial scale and a mapping rule of internal density distribution and spatial complexity aiming at the disaster spatial distribution form information; According to the mapping rule, converting the disaster space distribution form information into a space scale feature dimension and a space complexity feature dimension; extracting state transition nodes among different evolution stages and duration data of each evolution stage from the disaster evolution stage identification information; Calculating evolution rate mutation points based on the time intervals of the state transition nodes, and identifying a stability unbalance interval based on the fluctuation amplitude of the duration data; Determining the corresponding relation between the distribution density of the evolution rate mutation points and the characteristic dimension of the time evolution rate and the corresponding relation between the duration of the stability unbalance interval and the characteristic dimension of the stability, and obtaining the association rule of the evolution stage and the time characteristic; According to the association rule, the disaster evolution stage identification information is converted into a time evolution rate feature dimension and a stability feature dimension, and the spatial scale feature dimension, the spatial complexity feature dimension, the time evolution rate feature dimension and the stability feature dimension are combined to form a disaster feature dimension set.
4. The method of claim 1, wherein determining a constraint coupling relation expression for the set of multi-dimensional constraints, by which a mapping function between sensor operating parameters and the set of multi-dimensional constraints is determined, comprises: determining a demand boundary of the sensor working parameter based on the disaster monitoring demand constraint, and determining a limit boundary of the sensor working parameter based on the environmental adaptability constraint; determining a constraint conflict area with insufficient intersection between a sensor working parameter range required by disaster monitoring requirement constraint and a sensor working parameter range allowed by environmental adaptability constraint according to the requirement boundary and the limit boundary; calculating the deviation degree of the demand boundary and the limit boundary according to the constraint conflict area, and determining the priority coefficient of the disaster monitoring demand constraint and the environment adaptability constraint according to the deviation degree; performing weighted combination on the disaster monitoring demand constraint and the environment adaptability constraint based on the priority coefficient to determine a constraint coupling relation expression; and converting the constraint coupling relation expression into a boundary condition equation of the working parameters of the sensor, obtaining a feasible region boundary of the working parameters of the sensor by solving the boundary condition equation, and determining a mapping function between the working parameters of the sensor and the multi-dimensional constraint set.
5. The method of claim 1, wherein controlling the operating states of the sensors of the unmanned aerial vehicle based on the sensor operating parameter configuration scheme, driving the unmanned aerial vehicle to perform monitoring tasks along a predetermined route and collecting geological disaster detection data, comprises: extracting working mode setting parameters and data acquisition control parameters of each sensor from the sensor working parameter configuration scheme, converting the working mode setting parameters into a sensor starting instruction and a sensor working state switching instruction, and converting the data acquisition control parameters into a data acquisition frequency control instruction and a data acquisition precision control instruction; Respectively sending corresponding sensor starting instructions, sensor working state switching instructions, data acquisition frequency control instructions and data acquisition precision control instructions to each sensor carried by the unmanned aerial vehicle, so that each sensor enters a working state according to a sensor working parameter configuration scheme; Acquiring the position information and the time information of the navigation points of a preset navigation route, correlating the position information and the time information of the navigation points with the data acquisition frequency control instruction of each sensor, and determining the synchronous corresponding relation between a route propulsion node and a data acquisition triggering node, wherein the synchronous corresponding relation is used for representing a time sequence rule that the corresponding sensor is triggered to execute the data acquisition action when the unmanned aerial vehicle reaches the specific navigation point position; And driving the unmanned aerial vehicle to fly along the preset route, triggering a corresponding data acquisition triggering node when the unmanned aerial vehicle reaches a route pushing node defined in the synchronous corresponding relation, and controlling a corresponding sensor to acquire the geological disaster detection data.
6. A system for adaptive configuration of traffic geological disaster unmanned aerial vehicle sensors for implementing the method according to any of claims 1 to 5, comprising: the first unit is used for acquiring the geological disaster type characteristics and the environmental dynamic parameters of the target monitoring area; the second unit is used for carrying out capacity quantitative characterization on the multi-type sensors carried by the unmanned aerial vehicle based on a preset sensor performance constraint rule and detection capacity mapping relation to obtain a sensor capacity vector set; The third unit is used for processing each capacity vector in the sensor capacity vector set according to the geological disaster type characteristics, establishing a quantized adaptation relation between disaster characteristic dimensions and sensor capacity dimensions, and obtaining an adaptation metric matrix; a fourth unit, configured to perform collaborative solution by coupling multi-dimensional constraint according to the adaptive metric matrix and the environmental dynamic parameter, and generate a sensor working parameter configuration scheme; And the fifth unit is used for controlling the working state of each sensor of the unmanned aerial vehicle based on the sensor working parameter configuration scheme, driving the unmanned aerial vehicle to execute monitoring tasks along a preset route and collecting geological disaster detection data, wherein the geological disaster detection data are used for optimally adjusting the weight coefficient of the corresponding disaster characteristic dimension in the adaptive measurement matrix.
7. An electronic device, comprising: A processor; A memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to perform the method of any of claims 1 to 5.
8. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 5.

Description

Adaptive configuration method and system for traffic geological disaster unmanned aerial vehicle sensor Technical Field The invention relates to the technical field of geological disaster monitoring, in particular to a self-adaptive configuration method and system for a traffic geological disaster unmanned aerial vehicle sensor. Background With the frequent occurrence of natural disasters and the continuous promotion of traffic infrastructure construction, traffic geological disaster monitoring has become an important link for guaranteeing traffic safety. In recent years, unmanned aerial vehicles gradually become an important technical means for monitoring traffic geological disasters by virtue of the advantages of flexibility, wide coverage range, low cost and the like. Traditional traffic geological disaster monitoring mainly relies on manual on-site investigation or fixed monitoring equipment, and is low in efficiency and has potential safety hazards. The unmanned aerial vehicle is provided with a plurality of types of sensors for monitoring, so that multidimensional information of a disaster scene can be rapidly obtained, and important data support is provided for disaster evaluation and emergency decision. The unmanned aerial vehicle monitoring system is generally provided with a plurality of types of sensors such as an optical camera, an infrared thermal imager, a laser radar, a multispectral sensor and the like, and can acquire various disaster index data such as ground surface deformation, hydrologic characteristics, temperature change and the like. With the development of sensor technology, the technical performance of the unmanned aerial vehicle monitoring system is continuously improved, and the application range is wider and wider. However, the existing traffic geological disaster unmanned aerial vehicle monitoring technology still has the defects and shortcomings that the sensor configuration is not targeted, most systems adopt a fixed sensor combination scheme, and cannot be flexibly adjusted according to different types of geological disaster characteristics, so that the matching degree of monitoring data and actual disaster characteristics is not high, and the monitoring effect and the judging accuracy are affected. The sensor working parameter setting lacks environmental adaptability, and the influence of the environmental dynamic change on the sensor performance cannot be fully considered, for example, when the factors such as weather conditions, terrain complexity and the like are changed, the sensor working parameter cannot be automatically adjusted, so that the quality of the monitoring data is reduced in the complex environment. The prior art lacks a quantitative mapping mechanism between sensor capability and disaster characteristics, cannot realize accurate optimization of sensor configuration, often depends on manual experience setting, lacks scientific theoretical support and self-adaptive optimization capability, is difficult to meet high-efficiency accurate disaster monitoring requirements, and particularly is difficult to exert optimal monitoring efficacy in complex and changeable disaster environments. Disclosure of Invention The embodiment of the invention provides a self-adaptive configuration method and a self-adaptive configuration system for a traffic geological disaster unmanned aerial vehicle sensor, which can solve the problems in the prior art. In a first aspect of an embodiment of the present invention, there is provided a method for adaptively configuring a sensor of an unmanned aerial vehicle for a geological disaster of traffic, including: obtaining geological disaster type characteristics and environmental dynamic parameters of a target monitoring area; based on a preset sensor performance constraint rule and detection capability mapping relation, performing capability quantitative characterization on multiple types of sensors carried by the unmanned aerial vehicle to obtain a sensor capability vector set; Processing each capacity vector in the sensor capacity vector set according to the geological disaster type characteristics, and establishing a quantized adaptation relation between disaster characteristic dimensions and sensor capacity dimensions to obtain an adaptation metric matrix; according to the adaptive measurement matrix and the environment dynamic parameters, performing collaborative solution through coupling multi-dimensional constraint to generate a sensor working parameter configuration scheme; And controlling the working state of each sensor of the unmanned aerial vehicle based on the sensor working parameter configuration scheme, driving the unmanned aerial vehicle to execute monitoring tasks along a preset route and collecting geological disaster detection data, wherein the geological disaster detection data are used for optimally adjusting the weight coefficient of the corresponding disaster characteristic dimension in the adaptive measurement m