Method for managing an electrical power carrier based navigation light system

Abstract

The present application relates to the technical field of traffic management, and particularly relates to a method for managing a navigation light system based on a power carrier. The method comprises the following steps: obtaining flight plan data and real-time flight state data; performing light control demand evaluation according to the flight plan data and the real-time flight state data to obtain light demand evaluation data; obtaining basic data of the navigation light system, and performing navigation light scheduling according to the basic data of the navigation light system and the light demand evaluation data to obtain navigation light scheduling data; performing task area priority division according to the flight plan data to obtain flight task area priority data, and performing partition regulation and control according to the flight task area priority data and the navigation light scheduling data to obtain partition regulation and control data of the navigation light system, so as to perform auxiliary work for managing the navigation light system based on the power carrier. The present application realizes maximum utilization of navigation light resources, and achieves the goal of energy saving and high efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of traffic management, and particularly relates to a power carrier-based navigation light system management method. BACKGROUND

[0002] With the rapid development of the aviation transportation industry, the navigation light system of the airport plays a crucial role in ensuring flight safety and improving aviation efficiency. The navigation light system is mainly used for the take-off, taxiing and other flight tasks of the aircraft, ensuring that the aircraft can safely perform tasks under different weather, terrain and night conditions. However, the traditional navigation light system has some problems in scheduling, control and resource optimization, which needs to be improved. The traditional system cannot dynamically adjust according to the take-off time of the flight, the dynamic of the flight and the weather, etc., resulting in low efficiency of the navigation light system and serious waste of resources under different time and environmental conditions. SUMMARY

[0003] The present application relates to the technical field of traffic management, and particularly relates to a power carrier-based navigation light system management method.

[0004] The present application provides a power carrier-based navigation light system management method, comprising the following steps:

[0005] Step S1: obtaining flight plan data and real-time flight state data;

[0006] Step S2: evaluating the light control demand according to the flight plan data and the real-time flight state data to obtain light demand evaluation data;

[0007] Step S3: obtaining navigation light system basic data, and performing navigation light scheduling according to the navigation light system basic data and the light demand evaluation data to obtain navigation light scheduling data;

[0008] Step S4: dividing the priority of the flight task area according to the flight plan data to obtain flight task area priority data, and performing partition control according to the flight task area priority data and the navigation light scheduling data to obtain navigation light system partition control data, so as to perform power carrier-based navigation light system management auxiliary operation.

[0009] In the present application, according to the flight plan and the real-time state data of the flight, the light system can intelligently adjust the light switch, brightness and other parameters according to the take-off and landing time, type and other information of the aircraft, so that the aircraft is always in the appropriate lighting conditions during take-off and landing, avoiding the safety hazards caused by insufficient or excessive light. Through real-time light control demand evaluation, the light system can dynamically adjust the light switch and brightness according to the flight plan, flight status and different environmental conditions (such as day and night, weather, etc.), realize on-demand scheduling, and avoid unnecessary energy waste. Through flight task area priority division and integration of light scheduling data, the system can implement precise light zoning control in different areas. For example, at night, the light brightness of the staff area and the public area can be independently adjusted to avoid waste and improve work efficiency. Through power carrier technology, the light system can realize efficient communication and automatic scheduling with the power grid, reducing maintenance costs and personnel requirements. At the same time, the system can automatically identify faults or abnormal states, thereby realizing more efficient fault diagnosis and maintenance.

[0010] Preferably, step S1 is specifically:

[0011] Receiving the planned data of all flights from the airlines, air traffic control or other aviation data providers through the API interface to obtain preliminary flight plan data;

[0012] Obtaining preliminary real-time flight status data through data exchange with air traffic management systems and airline systems, wherein the preliminary real-time flight status data includes flight delay time, actual take-off and landing time and flight status information;

[0013] According to the preliminary flight plan data and the preliminary real-time flight status data, real-time verification is performed to obtain flight plan data and real-time flight status data, respectively.

[0014] In the present application, real-time data exchange is performed with airlines, air traffic control systems and other aviation data providers through API interface, ensuring the diversification of the sources of flight plan and real-time flight status data. By obtaining real-time data such as flight delay time and actual take-off and landing time, the light scheduling can be dynamically adjusted according to the actual situation, and the light system can respond to the latest situation during the actual take-off and landing of the flight, such as additional light support for delayed flights. By verifying the flight plan and real-time flight status, it can be avoided that the light scheduling does not match the situation when the flight status changes, so as to ensure that the take-off and landing process of the aircraft can be timely and appropriately supported by light, and the flight safety is improved.

[0015] Preferably, step S2 is specifically:

[0016] Flight feature extraction is performed according to flight plan data and real-time flight state data, and flight feature data is obtained, wherein the flight feature data includes aircraft type feature data, flight task data, flight time requirement data and flight surface data;

[0017] Light demand benchmark setting is performed according to the flight feature data, and light demand benchmark data is obtained;

[0018] Task area division is performed according to the flight task data and the flight surface data, and flight task area data is obtained;

[0019] Area demand evaluation is performed on the flight task area data, and flight task area demand data is obtained;

[0020] Weather condition data acquisition is performed according to the flight time requirement data, and flight weather condition data is obtained;

[0021] Illumination intensity and adjustment range setting is performed according to the flight weather condition data, the flight task area demand data and the light demand benchmark data, and light demand evaluation data is obtained.

[0022] In the present application, data such as aircraft type, flight task, time requirement and surface information are comprehensively extracted, and the system can understand the characteristics of each flight in detail, not only providing accurate input data for light demand evaluation, but also being able to conduct targeted light management according to the actual situation of different flights. By setting the light demand benchmark according to the flight feature data, the benchmark level of light illumination can be scientifically and accurately set, ensuring that the light intensity, illumination range, etc. meet the safety requirements of flight tasks. According to the weather conditions, task area demand and benchmark data calculation, the system can reasonably set the intensity and adjustment range of the light according to the actual demand, to adapt to different flight situations and environmental factors, so as to ensure that the light can cover the required area and meet the flight safety standards under different conditions. By dividing the area according to the flight task data and the surface data, the system can reasonably divide the area of the flight task, ensuring that the light management of each area is more accurate and targeted. For example, different areas such as take-off area and landing area require different intensity and brightness of light system, ensuring the detail and rationality of light scheduling. According to the specific data of the flight task area, demand evaluation is helpful to accurately understand the light demand of each area under different conditions (for example, some areas require additional light intensity under certain weather conditions).

[0023] Preferably, step S3 is specifically:

[0024] Obtaining aid light system basic data;

[0025] Performing node data processing according to the aid light system basic data, and obtaining aid light node data;

[0026] Demand mapping is performed based on navigation light node data and lighting demand assessment data to obtain navigation light demand mapping data;

[0027] Deviation analysis was performed based on navigation lighting demand mapping data and lighting demand assessment data to obtain lighting implementation deviation data;

[0028] The node network is constructed based on the navigation light node data to obtain the navigation light node network data;

[0029] The remaining lighting resources are calculated based on the navigation light node network data and the navigation light demand mapping data to obtain the remaining lighting resource data;

[0030] The remaining lighting resources are allocated based on the remaining lighting resource data and the lighting implementation deviation data to obtain the remaining lighting scheduling data;

[0031] The navigation light demand mapping data and the remaining light scheduling data are integrated to obtain navigation light scheduling data.

[0032] This invention maps lighting requirements based on lighting demand assessment data and combines this with deviation analysis to accurately identify and assess the gap between actual lighting needs and system output. This provides a scientific basis for resource scheduling, ensuring that the lighting needs of each flight are accurately met, avoiding over- or under-lighting, and guaranteeing flight safety. By calculating remaining lighting resources and combining them with deviation data for resource allocation, lighting is scheduled more intelligently, ensuring that resources are rationally allocated while meeting the needs of each mission area, avoiding unnecessary resource waste, and guaranteeing optimal lighting in the flight area. Lighting demand mapping, deviation analysis, and remaining resource allocation ensure that the lighting system can achieve precise control based on multiple factors such as the specific needs of the flight, the characteristics of the flight area, and weather conditions, avoiding insufficient or excessive lighting coverage. This helps pilots obtain optimal visual support under different conditions, improving flight safety. As flight plans change and flight status is updated, the lighting system can dynamically adjust the lighting, ensuring that during flight, the lighting can respond in a timely manner to the needs of takeoff and landing, road conditions, aircraft type, etc., ensuring that the lighting system is always in optimal condition to support safe takeoff and landing. By allocating lighting resources based on available data, the use of lights can be optimized, ensuring flight safety and effectively reducing energy consumption. For example, in low-demand areas (such as open or low-traffic areas), the intensity of lights can be reduced, or unnecessary lights can be turned off, thus reducing energy waste.

[0033] Preferably, the node data processing specifically includes:

[0034] Invalid data is filtered based on the basic data of the navigation lighting system to obtain the navigation lighting system filtered data;

[0035] The average brightness of the navigation lights is calculated by analyzing the filtered data of the navigation lights system.

[0036] Instantaneous anomaly identification is performed on the filtered data of the navigation lighting system to obtain instantaneous anomaly data of the navigation lighting;

[0037] The illumination range is evaluated based on the filtering data of the navigation lighting system, and the illumination range data of the navigation lighting system is obtained.

[0038] By integrating the navigation light system filter data, navigation light average brightness data, navigation light instantaneous anomaly data, and navigation light system illumination range data, the navigation light node data is obtained.

[0039] This invention significantly improves the accuracy and reliability of data in navigation lighting systems by removing invalid data (such as abnormal sensor values, expired or erroneous data). Calculating the average brightness of the lighting system helps balance illumination intensity within a given area, ensuring that it is neither too bright nor too dim. Through instantaneous anomaly identification of lighting data, the system can promptly detect malfunctions, damage, or operational abnormalities in lighting equipment (such as excessive fluctuations in light intensity or unstable power supply), providing a data foundation for the stability of the light source. Illumination range assessment helps dynamically adjust the illumination range based on environmental changes (such as weather, terrain, and aircraft type), avoiding insufficient or excessive illumination in certain areas and ensuring that the lighting system can automatically optimize according to actual flight requirements. By integrating the filtered data, average brightness data, anomaly detection data, and illumination range data of the lighting system, more comprehensive and accurate navigation light node data is obtained.

[0040] Preferably, the irradiation range assessment specifically includes:

[0041] Based on the filtered data of the navigation light system, the coordinates of the navigation light nodes and the ambient temperature and humidity of the navigation light environment are extracted to obtain the navigation light node coordinate data and the ambient temperature and humidity data of the navigation light environment, respectively.

[0042] Based on the coordinate data of the navigation light nodes, node images are acquired to obtain navigation light node image data;

[0043] Based on the image data of the navigation light nodes, terrain modeling of the navigation light nodes is performed to obtain the terrain model of the navigation light nodes;

[0044] Illumination simulation model of navigation light nodes is obtained by performing illumination simulation based on terrain model of navigation light nodes;

[0045] Based on the navigation light illumination simulation model, a preliminary data on the illumination range was obtained by simulating the navigation light illumination.

[0046] Based on the ambient temperature and humidity data and preliminary illumination range data of the navigation lights, the illumination path is tracked to obtain the illumination path data of the navigation lights;

[0047] The illumination attenuation data of the navigation light path is processed to obtain the illumination range data of the navigation light system.

[0048] This invention combines temperature and humidity data with lamp node coordinates to enable real-time assessment and optimization of the actual coverage area of ​​the lighting. By acquiring node coordinates and environmental data, and performing image acquisition and terrain modeling, the system can more accurately simulate the actual illumination range of each lamp node. Through illumination simulation and path tracing, the system can precisely calculate the propagation path and attenuation effect of the light, thereby obtaining accurate illumination range data. By processing the attenuation of the light path, the system can simulate the interaction between the light source and the ground, and predict the actual illumination effect of the lights under different environmental factors. Based on accurate illumination range data, the system can dynamically adjust the on / off range of the lights, thereby effectively saving energy without affecting flight safety.

[0049] Preferably, the lighting simulation specifically includes:

[0050] Navigation light source data is obtained by generating navigation light source data based on average brightness data and instantaneous anomaly data of navigation lights;

[0051] Light radiation transmission data is obtained by analyzing the light source data and the light simulation model of the navigation lights.

[0052] Based on the data of navigation light source and the simulation model of navigation light illumination, the interaction between the light source and the ground is analyzed to obtain data on the effect of light on the ground.

[0053] Obtain measured illumination data;

[0054] Based on the light radiation transmission data and the measured light data, deviation correction is performed to obtain the light radiation correction data.

[0055] Obtain ground reflectivity measurement data;

[0056] Based on the ground reflectivity measurement data and the data on the effect of sunlight on the ground, deviation correction is performed to obtain the corrected data on the effect of sunlight on the ground;

[0057] Preliminary data on the irradiance range are obtained by fusing the data on the correction of solar radiation and the correction data on the effect of solar radiation on the ground.

[0058] This invention combines average brightness data and instantaneous anomaly data of navigation lights to generate accurate light source data and ensure lighting accuracy during simulation. By simulating the radiation transmission path of light and the interaction between the light source and the ground, and considering factors such as terrain and obstacles, the system can accurately estimate the actual lighting effect. By acquiring measured lighting data in real time and performing deviation correction, the system can eliminate the error between actual illumination and theoretical simulation, ensuring that the light intensity meets the requirements of the flight mission. During the lighting simulation, the system considers the influence of factors such as ground reflectivity and corrects based on real-time measurement data, thereby simulating the lighting effect more accurately. By combining light radiation transmission data and ground reflectivity measurement data, the system can more accurately predict the illumination range and intensity of the lights, avoiding over-illumination or ineffective illumination, thus optimizing energy use. Through deviation correction and data fusion, the system can automatically adapt to environmental changes. Whether it is light intensity, ground reflectivity, or actual illumination effect, the system can adjust in real time to ensure that the aircraft receives accurate lighting support at all times.

[0059] Preferably, the node network construction specifically involves:

[0060] Based on the navigation light node data, a node spatial network is constructed to obtain the first navigation light node network data.

[0061] The communication topology network is constructed based on the navigation light node data to obtain the second navigation light node network data.

[0062] The functional network is constructed based on the navigation light node data to obtain the third navigation light node network data.

[0063] Based on the network data of the first navigation light node, the network data of the second navigation light node, and the network data of the third navigation light node, the node coordination relationship is processed to obtain the navigation light node network data.

[0064] This invention achieves multi-level network collaboration by considering spatial, communication, and functional dimensions in the node network construction. The network structure allows for more flexible and effective management of relationships between nodes, thereby improving the overall collaborative efficiency of the lighting system. For example, the spatial network focuses on the physical distribution and illumination range between nodes, the communication network focuses on the reliability and efficiency of data transmission between nodes, and the functional network ensures that each node performs precise control and scheduling according to actual tasks. Through the construction and collaborative relationship processing of the first, second, and third types of networks, the system can finely manage the interaction of lighting nodes based on different network models. For example, the spatial network optimizes the node layout, the communication network ensures efficient data transmission, and the functional network ensures logical coordination when nodes perform tasks, enabling networks with different functions to fully play their roles in operation and achieve more efficient collaboration and work scheduling.

[0065] Preferably, the calculation of remaining lighting resources is specifically as follows:

[0066] The remaining lighting power is calculated based on the remaining lighting resource data and the lighting implementation deviation data to obtain the remaining lighting power data;

[0067] The remaining illumination range data is obtained by calculating the remaining illumination range based on the remaining lighting resource data and the lighting implementation deviation data.

[0068] By integrating the remaining light power data and the remaining illumination range data, navigation light scheduling data is obtained.

[0069] This invention combines remaining lighting resources and lighting performance deviation data to more accurately calculate remaining lighting power and illumination range. This ensures that the lighting system maximizes the use of existing resources during mission execution, avoiding unnecessary waste. For example, when some lighting nodes deviate, the system can automatically adjust the remaining power and illumination range to ensure that lighting coverage is fully utilized within the flight mission area. The calculation of remaining lighting power and illumination range incorporates real-time data, enabling the lighting system to perform refined resource scheduling based on real-time needs during mission execution. Through real-time calculation and adjustment of remaining lighting power and illumination range, the system can react quickly to emergencies or flight changes. For instance, when some lighting equipment malfunctions or weather conditions change, the system can quickly adjust the remaining power and illumination range to ensure that the lighting needs of the flight mission area are not affected. By processing lighting performance deviation data, the system can intelligently identify and correct deviations, ensuring that the lighting needs of the flight mission are accurately met during mission execution. When calculating remaining lighting power and illumination range, the system considers the impact of lighting performance deviation data, allowing each node to dynamically adjust based on remaining resources when malfunctions or performance fluctuations occur.

[0070] Preferably, step S4 specifically includes:

[0071] Based on flight plan data, mission area priorities are divided to obtain flight mission area priority data.

[0072] Light control matching data is obtained by matching the flight mission area priority data and navigation light scheduling data.

[0073] Based on the lighting control matching data and the navigation lighting scheduling data, the flight status adjustment area control is performed to obtain the navigation lighting system zonal control data, so as to carry out auxiliary operations for the management of the navigation lighting system based on power line carrier.

[0074] This invention prioritizes mission areas based on flight plan data, allowing the system to prioritize mission areas with the most pressing lighting needs. By combining flight mission priorities with lighting scheduling data, the system can dynamically adjust lighting control in real time. For example, when a flight approaches or enters a complex weather zone, the system can automatically adjust the light intensity and distribution in the corresponding area to provide sufficient lighting support. During flight, the aircraft's state changes, such as speed, position, and weather conditions, leading to changes in flight paths and mission requirements. Based on flight mission area priority data, the system can adjust the working area of ​​the lighting system according to the importance of the area and actual needs, achieving intelligent zoning control. By combining flight mission area division with lighting scheduling data, the system can intelligently adjust the power allocation of each area.

[0075] The beneficial effects of this invention are as follows: By accurately integrating flight plan data and real-time flight status data, this invention can dynamically assess lighting control requirements based on the specific needs of each flight, ensuring that the lighting needs of each flight are precisely met, thereby avoiding over-lighting or under-lighting and significantly improving the utilization rate of lighting resources. By acquiring flight status data in real time (such as flight speed, heading, altitude, etc.), the lighting system can dynamically adjust according to changes in flight missions. For example, if a flight deviates or adjusts due to weather or air traffic control during flight, the system automatically adjusts the light intensity and distribution based on these changes, ensuring that pilots can obtain sufficient visibility under any circumstances and avoiding flight accidents caused by insufficient lighting. Using power line carrier-based technology for lighting scheduling has the advantages of high efficiency, low cost, and no need for additional wiring. It can transmit data and control signals on the basis of existing power lines, which not only reduces the infrastructure construction cost of the system but also improves the flexibility and scalability of the lighting system. In large-scale airports and surrounding areas, power line carrier can efficiently manage multiple lighting nodes, reducing the complexity and cost of traditional wiring and network construction. Attached Figure Description

[0076] Other features, objects, and advantages of this application will become more apparent from the following detailed description of the non-limiting embodiments, taken with reference to the accompanying drawings:

[0077] Fig. 1 A flowchart illustrating the steps of a navigation lighting system management method based on power line carrier communication according to an embodiment is shown.

[0078] Fig. 2 A flowchart illustrating the steps of a method for acquiring flight plan data and real-time flight status data according to an embodiment is shown.

[0079] Fig. 3 A flowchart illustrating the steps of a lighting control demand assessment method according to one embodiment is shown.

[0080] Fig. 4 A flowchart illustrating the steps of a navigational lighting scheduling method according to an embodiment is shown. Detailed Implementation

[0081] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0082] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. Functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0083] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0084] The international airport's navigational lighting system needs to provide different lighting support for each flight in different areas. The airport has two runways (A and B), and its flight schedule includes various flight missions during the day, night, and under different weather conditions. Four flights are expected to take off or land within 24 hours, with two requiring nighttime operations and the other two operating during the day. The mission times, types, and routes for each flight have been planned in advance. Flights 1 and 2 depart at 7 PM and 9 PM respectively, while flights 3 and 4 depart at 10 AM and 11 AM. Flights 1 and 3 are experiencing foggy weather, while flights 2 and 4 are flying in clear weather. Flight plan data is as follows: Flight 1: Departs at 7 PM, target runway A, flight time 60 minutes; Flight 2: Departs at 9 PM, target runway B, flight time 60 minutes; Flight 3: Departs at 10 AM, target runway A, flight time 70 minutes; Flight 4: Departs at 11 AM, target runway B, flight time 70 minutes. Real-time flight status data is as follows: Flight 1: Departed at 7:00 AM, delayed by 5 minutes, scheduled to depart at 7:05 AM. Flight 2: Departed at 9:00 AM, delayed by 10 minutes, scheduled to depart at 9:10 AM. Flight 3: Departed at 10:00 AM, on schedule. Flight 4: Departed at 11:00 AM, on schedule.

[0085] Flight 1: Night flight, foggy / hazy weather, medium-sized aircraft, requires strong takeoff and landing lighting. Flight 2: Night flight, clear weather, large aircraft, requires strong runway and landing lighting. Flight 3: Day flight, foggy / hazy weather, small aircraft, requires strong runway guidance lighting. Flight 4: Day flight, clear weather, medium-sized aircraft, requires moderate runway lighting.

[0086] Flight 1: Due to hazy weather, the runway and landing area lighting brightness is required to be increased to 2000 lux. Flight 2: In clear weather, the runway lighting brightness should be maintained at 1500 lux. Flight 3: During daytime hazy weather, the runway and guidance lights brightness should be increased to 1800 lux. Flight 4: During daytime clear weather, the runway lighting brightness should be maintained at 1000 lux.

[0087] Based on flight plans and weather conditions, flight zones for each flight are divided, and the required lighting intensity is assessed. Adaptive lighting intensities are set for each flight and different zones. The airport's lighting system comprises 24 lighting nodes distributed at both ends of the runway, taxiways, and the airport perimeter. The average brightness of each lighting node is calculated using sensor data, resulting in the system's brightness distribution. Abnormal lighting nodes are monitored and identified in real time to ensure rapid detection and adjustment of lighting malfunctions. The illumination range of each lighting node is assessed to ensure it meets the needs of each flight. Based on lighting demand assessment data, flight mission priorities, and mission area requirements, it is determined which lighting nodes need to operate at full capacity and which can maintain low power consumption. Through calculation, the most suitable lighting resources are allocated to each flight mission.

[0088] Flight 1 (Night, Fog / Haze): Altitude priority, allocate more lighting resources, especially in the takeoff and landing areas. Flight 2 (Night, Clear): Prioritize runway lighting and ground guidance lighting. Flight 3 (Day, Fog / Haze): Allocate sufficient lighting in the runway and guidance areas. Flight 4 (Day, Clear): Normal lighting resource allocation, reduce unnecessary energy consumption. Real-time data transmission and control signal transmission are achieved using power line carrier technology to ensure scheduling accuracy. Control signals are sent from the main control system to the lighting nodes via power lines to achieve precise lighting control. Light intensity and coverage are dynamically adjusted based on real-time flight status data (such as delay time, flight altitude, etc.). For example, if Flight 1 is delayed by 5 minutes, adjust the light brightness to ensure the takeoff and landing areas are always under optimal lighting conditions. Navigational lighting system zonal control data: Adjust lighting scheduling in each zone according to mission area priority and flight status to accurately meet the lighting needs of flight missions.

[0089] Please see Figs. 1 to 4 This application provides a management method for a navigation lighting system based on power line carrier, comprising the following steps:

[0090] Step S1: Obtain flight plan data and real-time flight status data;

[0091] Specifically, relevant data is obtained from the flight plan management system and the real-time flight monitoring system. Flight plan data typically includes information such as flight takeoff and landing times, routes, flight altitudes, and flight speeds; real-time flight status data includes real-time location information, flight speed, flight direction, flight status (e.g., takeoff, cruising, landing), and weather-related information. By interfaceing with the flight data center and the aviation management system, the system can acquire and process this data in real time.

[0092] Step S2: Based on flight plan data and real-time flight status data, conduct a lighting control requirement assessment to obtain lighting requirement assessment data;

[0093] Specifically, the system assesses lighting requirements based on flight plan data and real-time flight status data. Combining route information from the flight plan data, it determines the flight path and related airport and airspace areas. It evaluates the current flight phase (e.g., takeoff, cruise, landing) and determines whether navigation lights are needed based on the flight's real-time status. At night or in adverse weather conditions, pilots require stronger lighting to help identify runways or obstacles; therefore, lighting requirements can be dynamically adjusted by setting specific conditions (e.g., flight altitude below a certain value, poor weather conditions). Based on this assessment information, the system generates lighting requirement assessment data, including specific requirements parameters such as lighting intensity and duration for each flight segment and area.

[0094] Step S3: Obtain basic data of the navigation lighting system, and perform navigation lighting scheduling based on the basic data of the navigation lighting system and the lighting demand assessment data to obtain navigation lighting scheduling data;

[0095] Specifically, lighting scheduling is performed based on the fundamental data of the navigation lighting system and lighting demand assessment data. The fundamental data of the system is clearly defined, including the location, power, light type, and control interface of existing lighting equipment. The scheduling process considers the distribution of lighting equipment and matches it with the assessed demand data. Through analysis of the lighting demand assessment data and equipment distribution, the system determines the types and brightness of lights to be activated in specific areas and time periods. Simultaneously, based on the communication requirements of power line carrier communication, it ensures that the control signals of the lighting system can effectively communicate with the control equipment via power line carrier. Using power signal modulation, commands are sent through the power line carrier network to adjust the on / off, brightness, color, and other characteristics of the lights.

[0096] Step S4: Divide the mission area priority according to the flight plan data to obtain flight mission area priority data, and perform zone control according to the flight mission area priority data and navigation light scheduling data to obtain navigation light system zone control data, so as to carry out auxiliary operation of navigation light system management based on power line carrier.

[0097] Specifically, based on information such as flight routes, takeoff and landing locations, and mission areas in the flight plan data, mission areas are prioritized. The division of mission areas is based on factors such as flight routes, airport runways, and airspace control. The takeoff and landing areas of a particular flight require higher lighting priority, while other areas they pass through have relatively lower lighting requirements. The system will perform zoned control based on the priority of flight mission areas and lighting scheduling data. Specifically, for high-priority areas, the system will activate stronger lighting configurations and adjust brightness at appropriate times to ensure pilots receive the most suitable visual guidance during flight; for low-priority areas, lower lighting brightness or delayed lighting activation will be used to conserve energy. Lighting control signals based on power line carriers will be transmitted to different lighting subsystems. The lighting equipment in each area will respond according to the control signals, ensuring that lighting control meets the needs of flight safety and operational efficiency at different times and during different flight mission phases.

[0098] Preferably, step S1 specifically includes:

[0099] Step S11: Receive all flight planning data from airlines, air traffic control or other aviation data providers via API interface to obtain preliminary flight planning data;

[0100] Specifically, airlines typically provide interfaces containing flight schedules, including basic flight information such as flight number, departure and arrival times, route, aircraft type, and crew information. Data retrieval is performed using RESTful APIs or SOAP protocols to ensure the interface can return flight schedule data in real time.

[0101] Step S12: Obtain preliminary real-time flight status data by exchanging data with the air traffic management system and airline system. The preliminary real-time flight status data includes flight delay time, actual take-off and landing time and flight status information.

[0102] Specifically, the Air Traffic Management System (AMS) provides flight path and airspace control information. It exchanges flight schedule data with the Air Traffic Control (ATC) system via dedicated interfaces or standard protocols (such as AFTN, SITA, etc.). Airlines provide API interfaces for real-time status data, including actual takeoff and landing times, and flight status (e.g., in flight, taken off, arrived, delayed, etc.). The AMS typically provides flight location, status, and delay information through flight plan tracking systems (such as ADS-B, Radar, etc.). Data acquisition is achieved through direct exchange with the air traffic control center via protocols (such as AFTN or LDACS).

[0103] Step S13: Perform real-time verification based on the preliminary flight plan data and the preliminary real-time flight status data to obtain the flight plan data and the real-time flight status data respectively.

[0104] Specifically, the system verifies the consistency between flight plan data and real-time status data by comparing information such as flight number, departure time, and route. If inconsistencies are found (e.g., flight delays, route adjustments), the data is marked as abnormal for correction or re-acquisition. It ensures that flight numbers obtained from airline systems, ATC systems, and other data providers are consistent. It ensures that the planned departure time matches the actual departure time. If delays exceed the predetermined range, delay processing is implemented. The system determines whether there are delays or flight adjustments by comparing the actual takeoff and landing times in real-time status data with the planned data. If multiple data sources are available, the system prioritizes the data source with better signal quality. For example, it selects data provided by the airline as the primary data source and supplements and corrects it based on real-time information from the ATC system and other data sources. For anomalies occurring during data acquisition (e.g., missing or inconsistent status information from a data source), the system should handle them using pre-defined strategies (e.g., selecting an alternative data source or requesting re-acquisition of data) to ensure reliable flight plan and flight status data.

[0105] Preferably, step S2 specifically includes:

[0106] Step S21: Extract flight features based on flight plan data and real-time flight status data to obtain flight feature data, which includes aircraft type feature data, flight mission data, flight time requirement data, and flight road surface data.

[0107] Specifically, aircraft type characteristic data uses information such as aircraft model and type from flight data to determine the type and performance characteristics of the aircraft. The size, takeoff and landing performance, and lighting requirements of an aircraft are closely related. For example, large passenger aircraft and small jet aircraft have different lighting requirements; the latter requires lower lighting intensity, while the former requires higher lighting intensity. Flight mission data includes information such as the flight's takeoff and landing locations, route, and flight phases (takeoff, cruise, and landing), determining the specific objectives of the flight mission and the requirements of each flight phase. The requirements for navigational lighting vary greatly between different flight phases, with higher requirements during takeoff and landing and lower requirements during cruise. Flight time requirement data includes the flight's planned takeoff and landing times, actual takeoff and landing times, and flight delay information. Flight time requirements determine the flight's time period, thus affecting lighting requirements; for example, night flights require more lighting than daytime flights. Flight path data includes flight takeoff and landing routes, runway characteristics (such as length and smoothness), and the impact of weather conditions on the runway. Path smoothness and weather conditions affect the intensity and duration of lighting, especially during landing when runway surface conditions are poor, requiring increased lighting intensity.

[0108] Step S22: Set the lighting demand baseline based on flight characteristic data to obtain lighting demand baseline data;

[0109] Specifically, aircraft type and lighting requirements vary. Larger aircraft require higher intensity lighting due to their greater runway visibility requirements during takeoff and landing. Lighting benchmarks are set for different aircraft types, and the light intensity is adjusted based on the aircraft's characteristics. Flight mission phases and lighting requirements also differ. For example, landing phases require higher lighting, and the system determines the timing and intensity of lighting based on the flight phase. For instance, the lighting benchmark is higher during landing and lower during cruise. Time requirements also influence lighting needs. Night flights require more lighting support, so takeoff and landing times are taken into account when setting benchmarks. The lighting benchmark for night flights is set at 1.5 times the standard light intensity, while daytime flights maintain the standard light intensity.

[0110] Specifically, the system maps aircraft type characteristic data to a pre-defined aircraft type lighting standard library to obtain standard lighting data for each aircraft type. Then, it adjusts the lighting demand baseline based on flight mission data and flight time requirements to obtain lighting demand baseline data. The system maps aircraft model data to lighting standards. The mapping results are: large aircraft: lighting standard of 150 units; medium aircraft: lighting standard of 120 units; small aircraft: lighting standard of 80 units. The lighting demand baseline is then adjusted based on flight mission data and flight time requirements. Adjustments are made according to different flight phases, times (e.g., daytime or nighttime flights), and the urgency of the flight mission. Flight mission data includes takeoff and landing locations, flight missions (e.g., normal flight, emergency landing), and mission areas (e.g., airport runways, taxiways). If a flight is in an emergency (e.g., requiring an emergency landing), the lighting demand is increased to 1.5 times the standard lighting intensity. For normal missions, the lighting demand remains at the standard intensity. If the flight time is nighttime, the lighting demand baseline is increased to 1.5 times the standard lighting intensity. During daytime flights, lighting requirements are lower, therefore standard lighting intensity is maintained. Lighting requirement baseline = Aircraft type lighting standard data × Mission adjustment factor × Time adjustment factor. Mission adjustment factor: Normal mission: Factor 1. Emergency mission: Factor 1.5. Time adjustment factor: Daytime flight: Factor 1. Nighttime flight: Factor 1.5.

[0111] Step S23: Divide the mission area according to the flight mission data and the flight surface data to obtain the flight mission area data;

[0112] Specifically, based on flight mission data and runway data, flight mission areas are divided. Mission areas include specific areas during takeoff, landing, and flight, and different areas have different lighting requirements. For example, the lighting requirements for the runway area differ significantly from those for the airspace. The flight mission area is divided into several sub-areas, such as takeoff area, cruise area, and landing area. Each area is dynamically adjusted according to the real-time status of the flight to ensure the accuracy of lighting intensity and on / off control. In the landing area, especially on wet or foggy runways, lighting intensity needs to be increased. The runway data provides this information, and the system can automatically identify whether additional runway lighting is needed.

[0113] Step S24: Perform regional demand assessment on the flight mission area data to obtain flight mission area demand data;

[0114] Specifically, based on the current flight phase (takeoff, cruise, landing, etc.), a pre-defined rules engine assesses the lighting requirements for each area. For example, lighting requirements are higher during takeoff and landing, and lower during cruise. Weather factors directly impact regional lighting requirements. For instance, lighting requirements increase in rainy, snowy, or foggy conditions. By incorporating weather data, the system can dynamically adjust the lighting intensity for each area.

[0115] Specifically, during takeoff: runway and taxiway lighting requirements are 1.5-2 times the standard. During landing: runway visibility requirements are higher during landing, and lighting requirements are 1.5-2 times the standard. Cruising altitude is generally above 10,000 meters, at which point lighting requirements are lower, set to 0.5 times the standard to the standard. In foggy, rainy, or snowy weather: weather conditions reduce visibility, and lighting requirements should be increased to 1.5 times the standard. In clear weather: if weather conditions are good, lighting requirements are set according to the standard. The weather impact coefficient is the product of the weather impact factor and the flight phase adjustment factor; the regional lighting requirement is the base light intensity multiplied by the weather impact coefficient.

[0116] Step S25: Obtain weather condition data based on flight time requirements to obtain flight weather condition data;

[0117] Specifically, flight schedules are closely tied to weather conditions. By accessing weather data sources (such as weather station APIs and meteorological satellite data), the system can obtain real-time weather information for the areas the flight will pass through. Weather data includes information on cloud cover, wind speed, temperature, and visibility. This data is used to adjust lighting requirements.

[0118] Step S26: Based on flight weather data, flight mission area demand data, and lighting demand baseline data, set the light intensity and adjustment range to obtain lighting demand assessment data.

[0119] Specifically, the system calculates the required light intensity and adjustment range for each area. Taking into account the aircraft type, flight phase, time requirements, weather conditions, and the needs of the mission area, the system dynamically sets the light intensity range for different areas. For example, if the landing area is foggy and the weather is severe, the system sets the light intensity for that area to the maximum value, while maintaining standard brightness during the cruise phase.

[0120] The system acquires flight mission area data based on flight plans and specific requirements (such as flight paths, takeoff and landing points, and routes). This data includes the geographical location of the flight area (such as runways, taxiways, and high-altitude airways), the flight phase of each mission area (such as takeoff, cruise, and landing), and the area's priority (such as important airport runways and emergency landing zones). Weather factors (such as fog, rain, clouds, and visibility) directly affect the required lighting intensity. The system obtains real-time weather data through a weather monitoring system and adjusts lighting requirements accordingly. Lighting requirement baseline data is based on standard lighting design schemes provided by aviation facility or airport design specifications. Different types of aircraft and different flight phases require different lighting intensities and adjustment ranges. The system dynamically sets the lighting requirements for each area based on aircraft type and flight phase. The system sets the initial lighting intensity based on area priority, weather impact, flight phase, and aircraft type. For example, for landing areas (especially in foggy weather), the system sets the intensity to maximum (100%). For cruise areas, it sets it to standard brightness (such as 50%-70%). For takeoff areas, the intensity will be adjusted to a higher level based on weather conditions. The adjustment range is determined based on the geographical extent of the mission area, flight phase, and weather conditions. Typically, the light adjustment range refers to the area illuminated and the maximum coverage distance. For example, during aircraft landing, it's necessary to increase the light coverage area to ensure the visibility of ground markings, especially in low visibility conditions. Taking into account weather, aircraft, and mission area factors, for example, if the landing area is foggy or experiencing rain or snow, the system will automatically adjust the light intensity to the maximum based on real-time weather data, increasing the illumination range and adjusting the light distribution to ensure the pilot can clearly see the runway and surrounding ground conditions. Through these calculations, the system generates lighting requirement assessment data that includes specific light intensity, illumination range, adjustment range, and priority information for each area. For example, a landing area under adverse weather conditions may require the upper limit of light intensity (e.g., 100%) and a larger illumination range (e.g., 500 meters to both sides of the runway), while a cruise area only needs to maintain standard brightness and a smaller adjustment range.

[0121] Preferably, step S3 specifically includes:

[0122] Step S31: Obtain basic data for the navigation lighting system;

[0123] Specifically, the system needs to acquire basic data from the navigation lighting system. This basic data includes fundamental information about the lighting equipment, its location, power, illumination range, control method, and communication interface. Equipment information includes light type (e.g., runway lights, taxiway lights, marker lights), model, power, lifespan, and location coordinates. Lighting control information includes the switching method, dimming control method, whether power line carrier control is supported, and whether remote adjustment is supported. Communication network information involves the data exchange method between the lighting system and the control center, such as power line carrier communication networks and wireless communication protocols.

[0124] Step S32: Process the node data based on the basic data of the navigation lighting system to obtain the navigation lighting node data;

[0125] Specifically, the system processes data from each lighting node (such as an individual lamp or lighting control point) in the navigation lighting system, extracting key feature data for each node. Node data processing includes location data processing to determine the precise location of each lighting node, for example, by marking the geographic coordinates of the lighting equipment using GPS or a Geographic Information System (GIS). Control parameter processing handles the control parameters of each lighting node, including light power, brightness, dimming range, and on / off status. Performance data analysis analyzes the operating status of each node (such as whether it is malfunctioning or overloaded) and stores this data as the health status of the lighting node.

[0126] Step S33: Perform demand mapping based on navigation light node data and lighting demand assessment data to obtain navigation light demand mapping data;

[0127] Specifically, based on lighting demand assessment data, the system matches the demand of each lighting node with the actual capabilities of the lighting equipment to obtain lighting demand mapping data. According to the lighting demand of the area where each lighting node is located, the system assesses the required light intensity, illumination range, and duration for that node. For example, for runway lights, the intensity is adjusted to a higher level during nighttime or inclement weather, while for taxiway lights, the intensity is adjusted to a lower level. The demand is mapped to each lighting node, and it is determined whether the node's capabilities meet the demand. If a node's capabilities are insufficient to meet the demand, the system marks that node as inefficient and performs scheduling optimization. Because real-time flight status (such as flight delays and changes in takeoff and landing times) affects lighting demand, the system updates the demand mapping data in real time.

[0128] Step S34: Perform deviation analysis based on the navigation lighting demand mapping data and lighting demand assessment data to obtain lighting implementation deviation data;

[0129] Specifically, the deviation between lighting demand and actual supply is analyzed. Based on demand mapping data and actual lighting control capabilities, the lighting system's performance deviation is calculated for different areas and time periods. The deviation between actual and target illuminance is calculated. If the target illuminance is greater than the actual illuminance, the deviation is positive, indicating that the system has failed to meet demand; if the target illuminance is less than the actual illuminance, the deviation is negative, indicating that system resources are excessive. Deviation analysis considers not only differences in light intensity but also factors such as lighting switching timing and control precision. For example, in some areas, delayed switching times or improper brightness settings can also lead to deviations. The system dynamically adjusts its lighting control strategy based on the deviation data, such as increasing or decreasing the light intensity in certain areas, and optimizing the allocation of remaining lighting resources.

[0130] Step S35: Construct the node network based on the navigation light node data to obtain the navigation light node network data;

[0131] Specifically, the network structure of the lighting nodes is constructed according to their actual layout and function. The construction of the node network involves a systematic division and integration of the space and function of the lighting system. Lighting nodes are classified according to function (e.g., runway lights, taxiway lights, indicator lights, etc.) and physical location (e.g., north and south runways, east and west taxiways, etc.). The communication method between nodes is determined; for example, each node is connected via power line carrier or wireless network, ensuring that each node can receive signals from the central control system. The network topology of the lighting nodes is constructed to ensure that control signals can cover all lighting nodes, avoiding lighting control failures due to communication faults.

[0132] Step S36: Calculate the remaining lighting resources based on the navigation light node network data and the navigation light demand mapping data to obtain the remaining lighting resource data;

[0133] Specifically, the system calculates the remaining lighting resources based on node network data and demand mapping data. The calculation of remaining resources considers multiple factors, including satisfied demand, the operational status of each lighting node, and the results of deviation analysis. The system calculates the lighting resources already allocated to each area, including the intensity, quantity, and on / off status of the lights. Based on the demand mapping data, it determines which areas have had their lighting demands met and which have not. For areas with unmet demands, the system reallocates the remaining lighting resources. By calculating the number of remaining lighting nodes and their available power, the system obtains data on the remaining lighting resources. These resources can then be used in other areas with higher demand.

[0134] Step S37: Allocate remaining lighting resources based on remaining lighting resource data and lighting implementation deviation data to obtain remaining lighting scheduling data;

[0135] Specifically, the system redistributes remaining lighting resources based on deviation data to compensate for insufficient lighting in certain areas or optimize excess lighting resources in others. Based on the deviation analysis results, remaining resources are prioritized for areas where demand is not fully met. Priority is ranked according to factors such as flight density, flight phase (takeoff, landing), and weather conditions. If the lighting demand deviation in a certain area is significant, the system will prioritize allocating remaining resources to fill the demand gap and ensure flight safety. By adjusting light intensity or delaying on / off times, the remaining lighting resources can be optimally configured.

[0136] Step S38: Integrate the navigation light demand mapping data and the remaining light scheduling data to obtain navigation light scheduling data.

[0137] Specifically, the system integrates lighting demand mapping data with remaining lighting scheduling data to form navigation lighting scheduling data. The integrated data includes the following: area lighting requirements, the required light intensity, on / off time, and duration for each area; lighting resource allocation, determining the specific lighting resource configuration for each area based on the allocation results of remaining lighting resources.

[0138] Preferably, the node data processing specifically includes:

[0139] Invalid data is filtered based on the basic data of the navigation lighting system to obtain the navigation lighting system filtered data;

[0140] Specifically, the system checks the integrity and format of the data. For example, it checks for incorrect lighting equipment locations, negative power values, and abnormal switch states. Data with these issues is considered invalid. Based on historical equipment data and standard values, rules are defined to mark invalid data. For instance, if the brightness value of a lighting node is below the normal range, or if the power value of a node exceeds the maximum rated power limit, it will be marked as invalid. After filtering invalid data, the system deletes it, ensuring that the analysis is based only on valid data, resulting in filtered data for the navigation lighting system.

[0141] The average brightness of the navigation lights is calculated by analyzing the filtered data of the navigation lights system.

[0142] Specifically, the system extracts brightness data for each light node from the filtered data of the navigation lighting system. This brightness data is collected at specific time intervals, requiring time-based processing to calculate the average brightness of each node over different time periods. The system averages the brightness values ​​of each light node to obtain its average brightness. For example, for a particular light node, the system calculates the average of the brightness values ​​collected over the past 24 hours. To evaluate the effectiveness of the average brightness, the system compares it to a preset brightness standard. If the average brightness value of a light node is lower than expected, the system considers that the node needs increased brightness or maintenance.

[0143] Instantaneous anomaly identification is performed on the filtered data of the navigation lighting system to obtain instantaneous anomaly data of the navigation lighting;

[0144] Specifically, transient anomaly identification is used to detect sudden problems in the lighting system in real time, such as lights suddenly going out or abnormal brightness fluctuations. Based on historical data and normal operating status of the light nodes, the system sets several anomaly identification rules. For example, if the brightness value of a node suddenly drops by more than 50% in a short period, or if the node's status changes from "on" to "off" without a preset command, these are considered anomalies. The system continuously monitors the status data of each node and compares it with each data acquisition to detect any abnormal data fluctuations. Abnormal changes in brightness and power values ​​are immediately marked as "transient anomalies." Once an anomaly is identified, the system uses a decision tree model trained on historical data to classify it, distinguishing between different types of anomalies such as "power anomaly," "brightness decrease," or "equipment malfunction."

[0145] The illumination range is evaluated based on the filtering data of the navigation lighting system, and the illumination range data of the navigation lighting system is obtained.

[0146] Specifically, the illumination range assessment analyzes the illumination coverage area of ​​each light node, determines the gap between the actual and expected coverage area, and optimizes insufficient areas. The system combines the geographic location information of each light node (e.g., using GPS coordinates or map data) to determine its coverage area. The illumination range of a light node is a circular area centered on the node, with the radius related to its illumination capacity. Based on the node's light intensity and illumination angle, the system calculates the actual illumination range of each light node, including factors such as the node's illumination radius and illumination angle, to help assess whether the actual illumination range meets standards. The calculated illumination range is compared with the requirements of the flight area to analyze whether there are any blind spots or overlapping areas. For example, does the illumination range on both sides of the runway cover the taxiway, or is the light intensity in certain areas too strong?

[0147] By integrating the navigation light system filter data, navigation light average brightness data, navigation light instantaneous anomaly data, and navigation light system illumination range data, the navigation light node data is obtained.

[0148] Specifically, the system integrates the various data obtained in the preceding steps to form data for each light node, resulting in navigation light node data. The system matches and integrates the "filtered data," "average brightness data," "instantaneous anomaly data," and "illumination range data" for each light node. Using the node ID, the system merges all relevant data for each node to form a complete light node data package. The integrated data undergoes a consistency check to ensure no data omissions or errors. For example, if a node's brightness data exhibits abnormal fluctuations that are not identified as "instantaneous anomalies," the system will recalibrate the data. The data for each light node will be output in a standard format for subsequent demand assessments and scheduling decisions. The integrated navigation light node data will include information such as the basic status, average brightness, anomalies, and illumination range of each node, providing a precise basis for optimizing the lighting system's scheduling.

[0149] Preferably, the irradiation range assessment specifically includes:

[0150] Based on the filtered data of the navigation light system, the coordinates of the navigation light nodes and the ambient temperature and humidity of the navigation light environment are extracted to obtain the navigation light node coordinate data and the ambient temperature and humidity data of the navigation light environment, respectively.

[0151] Specifically, the first step in illumination range assessment is to acquire basic location and environmental data for the light nodes, both of which are crucial factors affecting illumination range calculation. Geographic coordinates (e.g., GPS coordinates or map-based coordinates) for each light node are extracted from the filtered data of the navigational lighting system. These coordinates are used for terrain modeling and illumination range simulation. The coordinate data is typically represented in three-dimensional spatial coordinates of longitude, latitude, and elevation. Ambient temperature and humidity directly affect light propagation efficiency. Real-time temperature and humidity data are extracted from meteorological data sources (such as airport weather stations or sensor networks). This data will influence the degree of light attenuation and illumination effect.

[0152] Based on the coordinate data of the navigation light nodes, node images are acquired to obtain navigation light node image data;

[0153] Specifically, the system utilizes geographic information and camera equipment (such as aerial photography, drones, or fixed monitoring equipment) to collect image data of the areas where the light nodes are located, helping to build a visual model of the area. Based on the coordinates of each light node, the system controls the camera equipment or drone to capture images of its surrounding environment, obtaining image data. This image data includes terrain information from the ground, obstacles (such as buildings, trees, etc.), and aerial views. The image data corresponding to each node is integrated into the system database and geographically labeled to ensure that each image is associated with a specific light node and its location.

[0154] Based on the image data of the navigation light nodes, terrain modeling of the navigation light nodes is performed to obtain the terrain model of the navigation light nodes;

[0155] Specifically, by processing and analyzing image data, the system performs terrain modeling for the environment of each light node, establishing a 3D terrain model. The system processes the acquired images, extracting features such as ground height, obstacle location, and terrain undulation, including edge detection, depth map analysis, and image segmentation, identifying high and low points in the terrain. Using the extracted terrain features, combined with the coordinate information of the light nodes, a 3D terrain model is constructed, including the height information of the ground, buildings, and other obstacles, simulating a realistic terrain environment. This 3D terrain model is then combined with the coordinate data of the light nodes to form a complete geospatial model, providing a foundation for lighting simulation.

[0156] Illumination simulation model of navigation light nodes is obtained by performing illumination simulation based on terrain model of navigation light nodes;

[0157] Specifically, after the terrain model is established, the system uses lighting simulation technology to evaluate the illumination effect of each light node, simulating the propagation path, light intensity, and range of the light source. Based on parameters such as the type, power, beam angle, and illumination range of the light node, the system establishes a mathematical model of the light source. The light intensity of each light node is simulated based on factors such as its power and beam angle. According to the terrain model, the system simulates how the light propagates from the source to the ground. The model takes into account factors such as ground undulations and obstacle obstruction, calculating the light intensity and coverage of different areas. The lighting propagation model generates a lighting effect map for each light node, displaying the brightness distribution of each area.

[0158] Based on the navigation light illumination simulation model, a preliminary data on the illumination range was obtained by simulating the navigation light illumination.

[0159] Specifically, based on the simulation model, the system further calculates the actual illumination range of each light node in detail, obtaining preliminary illumination range data. The system calculates the illumination range of each light node point by point, simulating the light intensity at different locations, and considering factors such as light attenuation, reflection, and scattering, to calculate the illumination coverage area of ​​each node and generate an illumination intensity distribution map. Based on the simulation results, the system obtains the illumination range and illuminance distribution of each light node, generating preliminary illumination range data, including information such as the area of ​​illumination coverage and the distribution of light intensity.

[0160] Based on the ambient temperature and humidity data and preliminary illumination range data of the navigation lights, the illumination path is tracked to obtain the illumination path data of the navigation lights;

[0161] Specifically, by combining environmental temperature and humidity data, the propagation path of light is further tracked to accurately predict light attenuation and path loss. When light propagates in the air, it is affected by environmental factors (such as temperature, humidity, and wind speed). The system simulates the light attenuation effect in the air based on temperature and humidity data and a weighted formula. Higher temperatures result in faster light propagation, but higher humidity leads to increased light attenuation. Tracking algorithms (such as ray tracing) are used to simulate the propagation path of light after it originates from the light node. By calculating the interaction of light with different objects (such as the ground and buildings), the system tracks how light propagates to the ground and its intensity changes. The system records each light path during the simulation process, generating navigation light path data that describes how light diffuses in different areas, changes in light intensity, and their correlation with environmental factors.

[0162] The illumination attenuation data of the navigation light path is processed to obtain the illumination range data of the navigation light system.

[0163] Specifically, based on the tracked light path data, the system performs light attenuation processing to obtain illumination range data. Considering factors such as light reflection, refraction, and scattering, an attenuation model is applied to reduce the light intensity of each light path. The attenuation model corrects the light intensity based on parameters such as air humidity, temperature, and light propagation distance. Based on the attenuated illumination data, the system determines the effective illumination range of each light node and corrects the light intensity in different areas. The system generates illumination range data for the navigation lighting system, including the illumination area, illuminance distribution, and light attenuation of each light node.

[0164] Preferably, the lighting simulation specifically includes:

[0165] Navigation light source data is obtained by generating navigation light source data based on average brightness data and instantaneous anomaly data of navigation lights;

[0166] Specifically, by collecting average brightness data and instantaneous anomaly data of the navigation lights, the system first calculates the actual brightness of each light node. For some nodes, if there are instantaneous brightness anomalies (such as lights suddenly going out or being too dim), the anomaly data will be used to correct the power or brightness value of the light source. Based on the average brightness of each light node, the system will generate basic data of the light source according to the power and radiation range of the light source. The system will determine information such as the illuminance, beam angle, illumination range, and duration of light for each light node. These parameters will constitute the navigation light source data, serving as input for the illumination simulation. The light source data for each light node will include illuminance, beam angle, effective illumination range, and illumination characteristics adjusted for any anomalies.

[0167] Light radiation transmission data is obtained by analyzing the light source data and the light simulation model of the navigation lights.

[0168] Specifically, light radiation transmission is the core process of lighting simulation, which simulates how the radiation from the light source propagates to the target area.

[0169] Radiative Propagation Model: This model describes how light emitted from a light source propagates through air, the ground, or other objects. The system considers factors such as scattering and absorption in the air, calculating the transmitted light intensity by simulating the propagation path and attenuation of the light. During the simulation, the system divides the light transmission process into a spatial grid, calculating the change in light intensity within each grid cell. Based on different transmission distances, environmental conditions, and the characteristics of the light source, the system derives radiative transmission data, simulating how light gradually attenuates. The resulting "light radiative transmission data" includes the radiative intensity, propagation distance, and environmental influences of each light source at different spatial locations.

[0170] Based on the data of navigation light source and the simulation model of navigation light illumination, the interaction between the light source and the ground is analyzed to obtain data on the effect of light on the ground.

[0171] Specifically, after the light source radiates onto the ground, the interaction between the light and the ground affects the illumination effect. The interaction mechanism between light and the ground is simulated, primarily involving reflection, refraction, and absorption. The system establishes an interaction model between the light source and the ground, simulating how light is reflected, absorbed, or refracted by ground materials (such as grass, concrete, asphalt, etc.). Reflectivity and absorptivity vary depending on the different ground characteristics. The reflectivity and absorptivity of each ground material can be found through experimental data or literature, or obtained through on-site measurements. Based on this data, the system simulates the reflection and absorption of light by different ground materials, calculating the actual intensity of the light's effect. The data on the effect of light on the ground will include how the light intensity at each light node affects the ground, particularly the variation in light intensity across different ground types.

[0172] Obtain measured illumination data;

[0173] Specifically, in real-world scenarios, the system uses light sensors or measuring devices to periodically collect actual light intensity data for each light node or monitored area. This data is typically collected at specific points in time to compare with simulation results.

[0174] Based on the light radiation transmission data and the measured light data, deviation correction is performed to obtain the light radiation correction data.

[0175] Specifically, illumination radiation correction aims to ensure consistency between simulated and actual data by adjusting the simulation results to reduce errors. By comparing simulated illumination radiation transmission data with measured illumination data, the system identifies the errors between the two. These errors manifest as overestimation or underestimation of intensity, caused by environmental changes, data acquisition errors, or inaccurate model assumptions. Based on error analysis, the system adjusts the simulated data. For example, it corrects model parameters such as illumination attenuation factor, light source brightness, and reflectivity based on deviations from measured data, ensuring that the simulation results better reflect reality. The corrected illumination radiation data will be more accurate and effectively reflect the actual illumination distribution.

[0176] Obtain ground reflectivity measurement data;

[0177] Specifically, the system measures light reflectance on different surfaces (such as grass, asphalt, and soil) using sensors or experimental equipment. This is achieved by illuminating the surface with a light source of a certain intensity and measuring the intensity of the reflected light under controlled conditions.

[0178] Based on the ground reflectivity measurement data and the data on the effect of sunlight on the ground, deviation correction is performed to obtain the corrected data on the effect of sunlight on the ground;

[0179] Specifically, ground reflectivity correction aims to improve the accuracy of lighting simulation by adjusting the simulated ground lighting effect through calibration of ground reflectivity. The system compares the measured reflectivity data with the simulated reflectivity to identify deviations caused by differences in ground type and actual reflectivity. Based on the reflectivity data, the system adjusts the simulated ground lighting effect data. By correcting the reflection intensity, the system can more accurately simulate the distribution and intensity of light on the ground. After adjustment, the system generates ground lighting effect correction data that reflects the true interaction between light and the ground.

[0180] Preliminary data on the irradiance range are obtained by fusing the data on the correction of solar radiation and the correction data on the effect of solar radiation on the ground.

[0181] Specifically, the system fuses the radiometrically corrected and terrestrially corrected data, calculating the illumination range based on information such as the light intensity and illumination range of each node. During the fusion process, the system considers factors such as light intensity, ground reflection characteristics, and transmission distance in different areas to obtain a more accurate illumination range. The preliminary illumination range data obtained includes information such as the effective illumination range, illuminance distribution, and light intensity of each light node.

[0182] Preferably, the node network construction specifically involves:

[0183] Based on the navigation light node data, a node spatial network is constructed to obtain the first navigation light node network data.

[0184] Specifically, the system calculates the distance between any two navigation light nodes based on their spatial coordinates (such as longitude, latitude, and altitude), using Euclidean distance or the spherical distance formula for geographic coordinates. Based on the distances between nodes, the system defines a threshold; only nodes with distances less than this threshold are considered adjacent. The threshold is adjusted according to the system's actual needs, such as considering only communication or lighting coordination between adjacent lights. All adjacent nodes are connected by edges in graph theory, forming a spatial network structure. Each node represents a light node, and the edges between nodes represent their spatial relationships, resulting in the first navigation light node network data, which includes the spatial positional relationships and connection rules between nodes.

[0185] The communication topology network is constructed based on the navigation light node data to obtain the second navigation light node network data.

[0186] Specifically, the communication topology network construction focuses on the communication connections and data exchange paths between light nodes, ensuring efficient communication between all nodes in the system. By analyzing the signal transmission and reception capabilities of each light node, the system calculates the effective communication range of each node based on its physical range. The communication range is estimated based on a signal strength attenuation model and is affected by terrain, environmental factors, and communication technologies (such as Wi-Fi, Zigbee, etc.). Based on the communication range of each node, the system determines which light nodes can communicate directly. If the communication ranges of two nodes overlap, they will form a connection in the topology network, and the resulting network structure is the second navigation light node network data. The system further optimizes the communication topology, constructing a multi-layered topology structure based on factors such as distance between nodes and communication quality. For example, some nodes act as master nodes or gateway nodes, responsible for forwarding data, while other nodes act as ordinary nodes, communicating only directly with surrounding nodes. The second navigation light node network data will include information such as communication relationships between nodes, signal strength, and communication quality, providing efficient data exchange paths for collaborative work.

[0187] The functional network is constructed based on the navigation light node data to obtain the third navigation light node network data.

[0188] Specifically, the functional network construction involves organizing nodes into a function-based network structure according to their functional requirements and assigned tasks. Each light node has different functional requirements; for example, some light nodes undertake functions such as task allocation, data acquisition, and lighting adjustment. The system categorizes nodes based on their functional requirements, such as categorizing them into lighting nodes, control nodes, and data collection nodes. The system connects nodes with similar or complementary functions based on their functional requirements; for example, lighting nodes may form functional connections with control nodes and sensor nodes. The edges of the functional network represent the functional dependencies between nodes. The functional network presents a multi-level structure, with higher-level nodes responsible for coordinating and controlling the entire system, while lower-level nodes perform specific operations. The system hierarchically divides these functions and constructs corresponding network structures based on the requirements of different levels. The third-level navigation light node network data will include the functional type, functional requirements, and functional dependencies of each node.

[0189] Based on the network data of the first navigation light node, the network data of the second navigation light node, and the network data of the third navigation light node, the node coordination relationship is processed to obtain the navigation light node network data.

[0190] Specifically, the system needs to integrate data from spatial networks, communication networks, and functional networks. Conflicts exist between different networks; for example, some nodes may be spatially adjacent but functionally incompatible. The system will resolve these conflicts based on factors such as node priority, functional requirements, and distance, determining the role of each node within the overall network. The system establishes collaborative relationships between nodes by comprehensively considering their spatial location, communication capabilities, and functional requirements. Using graph theory or optimization algorithms, the optimal connection method for each node in collaborative work is calculated to ensure efficient cooperation among all nodes in the system. Based on collaborative relationship processing, the system assigns a clear role to each node, such as a master node, slave node, or bridging node. The master node is responsible for coordinating and scheduling tasks, while slave nodes execute specific operations. The system optimizes the allocation of these roles to ensure tasks are completed efficiently according to priority. The resulting navigation light node network data includes comprehensive information such as the spatial location, communication connections, functional dependencies, and collaborative relationships of each light node.

[0191] Preferably, the calculation of remaining lighting resources is specifically as follows:

[0192] The remaining lighting power is calculated based on the remaining lighting resource data and the lighting implementation deviation data to obtain the remaining lighting power data;

[0193] Specifically, the system acquires the initial power and current remaining power resources of each light node. This data is obtained through a real-time monitoring system (such as power monitoring equipment or a power meter). The system compares the remaining power of each light node with the actual power consumption of the lights to obtain preliminary remaining power data. The system then adjusts the remaining power of each node based on this deviation data. For example, if the actual brightness of a light node is lower than expected, the system will reduce the power of that node; conversely, it will increase its power. By comprehensively considering the remaining light resource data and the power value after deviation correction, the system calculates the remaining power of each light node. The remaining power data includes the maximum power that each node can provide in the current state, and the remaining light power data will include the power allocation value for each light node.

[0194] Specifically, and more importantly, the remaining lighting power data includes first remaining lighting power data and second remaining lighting power data. The calculation of remaining lighting power is as follows: based on the remaining lighting resource data and lighting implementation deviation data, complementary remaining lighting power calculation and overlapping remaining lighting power calculation are performed to obtain the first remaining lighting power data and the second remaining lighting power data; Complementary remaining lighting power = Remaining lighting resource data - Lighting implementation deviation data. When calculating complementary remaining lighting power, the lighting implementation deviation data is subtracted from the remaining lighting resource data. Deviation represents certain losses or inefficiencies, and this part of the power cannot be effectively utilized. Overlapping remaining lighting power = Complementary remaining lighting power + Redundant power / Overlapping system compensation. Redundant power refers to the excess power reserved to ensure stable system operation, which comes from multiple lighting systems or backup power supplies. This compensation amount needs to be added to the complementary remaining lighting power during calculation, and the data comes from a pre-set database.

[0195] The remaining illumination range data is obtained by calculating the remaining illumination range based on the remaining lighting resource data and the lighting implementation deviation data.

[0196] Specifically, based on the remaining power of each light node, the system estimates the basic illumination range of each node. The system estimates an initial illumination range based on the remaining power of each node. The system uses light performance deviation data to correct the illumination range. Deviation data includes reductions in illumination range caused by light performance degradation, beam angle changes, and environmental factors. Through analysis of the deviation data, the system adjusts the initial illumination range estimate. Based on the adjusted data, the system further optimizes the illumination range calculation to ensure that each light node can cover its intended area or maximize the use of remaining resources. For some light nodes, further corrections are made based on surrounding environmental conditions (such as buildings or terrain obstacles). The system allocates the illumination range to the entire area based on the remaining illumination range calculation results of each light node, ensuring that each area receives appropriate light intensity. The remaining illumination range data includes information such as the illumination area, coverage area, and adjusted illumination intensity of each light node, providing data support for further scheduling of light resources.

[0197] By integrating the remaining light power data and the remaining illumination range data, navigation light scheduling data is obtained.

[0198] Specifically, the system correlates the remaining power of each light node with its illumination range data. A node's illumination range and power are interrelated; higher-powered light nodes can cover a wider area. Therefore, the system considers the balance between power and illumination range, ensuring that high-powered nodes effectively cover larger areas, while low-powered nodes focus on smaller areas. The system matches the illumination demand of each area with the remaining lighting resources. For areas with high illumination demand, the system prioritizes allocating higher-powered light nodes. For areas with low illumination demand, the system uses lower-powered light nodes with shorter illumination ranges. By combining the calculation results of power and illumination range, the system performs resource scheduling optimization to ensure that the resources of each node are used most rationally. For example, if a node has a lot of remaining power but a small illumination range, the system will adjust it to an area that needs more light or increase its illumination range to cover more areas. Based on the actual demand data and calculation results, the system generates navigation lighting scheduling data. This scheduling data includes power allocation, illumination area allocation, and area priority for each light node, ensuring that the lighting system maximizes resource utilization while meeting the lighting needs of each area. The navigation lighting scheduling data will include detailed lighting resource allocation plans, power values ​​of each node, illumination range, and area coverage, serving as the basis for further system operations.

[0199] Preferably, step S4 specifically includes:

[0200] Step S41: Divide the mission area priority according to the flight plan data to obtain the flight mission area priority data;

[0201] Specifically, the purpose of mission area prioritization is to dynamically assign priorities to each area based on the importance and needs of different mission areas involved in the flight plan, thereby ensuring that the lighting needs of critical areas are met first during flight. The system first obtains the specific areas involved in all flight missions through flight plan data. Depending on the characteristics of the area (such as airport runways, taxiways, and airways), the lighting requirements of each area will differ. For areas critical to flight safety (such as runways and important airways), the system identifies high-priority areas based on takeoff and landing times, flight distances, and other data in the flight plan. Based on the urgency of the area, flight time, and flight distance, the system assigns a priority to each mission area. Higher priority areas typically include takeoff and landing runways and the airspace around the airport. Low-priority areas are areas such as airways during flight that do not significantly affect flight safety. Priority assignment is usually based on pre-defined rules or obtained through historical data analysis. Using flight plan data and mission requirements, the system generates flight mission area priority data based on the priority requirements of the mission areas. This data provides a basis for decision-making in lighting scheduling and control.

[0202] Step S42: Perform light control matching based on flight mission area priority data and navigation light scheduling data to obtain light control matching data;

[0203] Specifically, the system analyzes the lighting requirements of each flight mission area based on priority data. For example, higher-priority areas require stronger illumination power and a wider illumination range, while lower-priority areas have lower requirements. By analyzing flight plan data, the system can identify the specific lighting needs of each area. The system then matches the lighting requirements of each area with previously obtained navigation lighting scheduling data. This lighting scheduling data includes information such as the power allocation and illumination range of lighting nodes. By comparing the remaining resources and illumination capabilities of each lighting node, the system determines which lighting nodes can meet the needs of higher-priority areas and assigns these nodes to the corresponding mission areas. The system generates lighting control matching data, which includes information such as each area and its corresponding lighting nodes, power allocation, and illumination range. This control matching data ensures that the lighting system can rationally allocate lighting resources according to the priority of the mission areas.

[0204] Step S43: Perform flight status adjustment area control based on lighting control matching data and navigation lighting scheduling data to obtain navigation lighting system zonal control data, so as to carry out auxiliary operations for navigation lighting system management based on power line carrier.

[0205] Specifically, the system needs to monitor flight status data in real time, including the flight's current position, altitude, and speed. Through a connection to the real-time flight status data interface, the system can continuously acquire various information during flight and dynamically adjust the control strategy for lighting areas based on this information. According to the flight status, the system will dynamically adjust the lighting control of each task area. For example, if an aircraft approaches a high-priority area (such as a runway or taxiway), the system will automatically increase the brightness and illumination range of the lights in that area to ensure flight safety. For low-priority areas during flight, the system will reduce or turn off the lighting in those areas. The system will further optimize the allocation of lighting resources based on real-time flight status and lighting control matching data. For example, if a change in the flight status of a certain area leads to a reduction in the lighting demand for that area, the system will allocate the remaining lighting resources to higher-priority areas to ensure optimal resource utilization. The navigation lighting system zoning control data generated by the system includes adjustment strategies based on flight status and task area priorities, containing lighting control parameters for each area (such as power, illumination range, brightness, etc.). This data will be used in the actual lighting scheduling system to ensure precise management and allocation of lighting resources.

[0206] Therefore, the embodiments should be regarded as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended application documents rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of the equivalents of the application documents be incorporated into the invention.

[0207] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A management method for a navigation lighting system based on power line carrier communication, characterized in that, Includes the following steps: Step S1: Obtain flight plan data and real-time flight status data; Step S2: Based on flight plan data and real-time flight status data, conduct a lighting control requirement assessment to obtain lighting requirement assessment data; Step S3: Obtain basic data of the navigation lighting system; process node data based on the basic data of the navigation lighting system to obtain navigation light node data; perform demand mapping based on the navigation light node data and lighting demand assessment data to obtain navigation light demand mapping data. Deviation analysis is performed based on navigation light demand mapping data and lighting demand assessment data to obtain lighting implementation deviation data; a node network is constructed based on navigation light node data to obtain navigation light node network data; and remaining lighting resources are calculated based on navigation light node network data and navigation light demand mapping data to obtain remaining lighting resource data. The remaining lighting resources are allocated based on the remaining lighting resource data and the lighting implementation deviation data to obtain the remaining lighting scheduling data; The navigation light demand mapping data and the remaining light scheduling data are integrated to obtain navigation light scheduling data; Step S4: Divide the mission area priority according to the flight plan data to obtain the flight mission area priority data, and perform zone control according to the flight mission area priority data and the navigation light scheduling data to obtain the navigation light system zone control data, so as to carry out auxiliary operation of navigation light system management based on power line carrier. The specific process for node data processing is as follows: Invalid data is filtered based on the basic data of the navigation lighting system to obtain the navigation lighting system filtered data; The average brightness of the navigation lights is calculated by analyzing the filtered data of the navigation lights system. Instantaneous anomaly identification is performed on the filtered data of the navigation lighting system to obtain instantaneous anomaly data of the navigation lighting; The illumination range is evaluated based on the filtering data of the navigation lighting system, and the illumination range data of the navigation lighting system is obtained. By integrating the navigation light system filter data, navigation light average brightness data, navigation light instantaneous anomaly data, and navigation light system illumination range data, we obtain navigation light node data. The assessment of the irradiation range specifically includes: Based on the filtered data of the navigation light system, the coordinates of the navigation light nodes and the ambient temperature and humidity of the navigation light environment are extracted to obtain the navigation light node coordinate data and the ambient temperature and humidity data of the navigation light environment, respectively. Based on the coordinate data of the navigation light nodes, node images are acquired to obtain navigation light node image data; Based on the image data of the navigation light nodes, terrain modeling of the navigation light nodes is performed to obtain the terrain model of the navigation light nodes; Illumination simulation model of navigation light nodes is obtained by performing illumination simulation based on terrain model of navigation light nodes; Based on the navigation light illumination simulation model, a preliminary data on the illumination range was obtained by simulating the navigation light illumination. Based on the ambient temperature and humidity data and preliminary illumination range data of the navigation lights, the illumination path is tracked to obtain the illumination path data of the navigation lights; The illumination attenuation data of the navigation light path is processed to obtain the illumination range data of the navigation light system.

2. The method according to claim 1, characterized in that, Step S1 is as follows: Preliminary flight plan data is obtained by receiving all flight planning data from airlines, air traffic control, or other aviation data providers through API interfaces. By exchanging data with air traffic management systems and airline systems, preliminary real-time flight status data is obtained, which includes flight delay time, actual takeoff and landing time, and flight status information. Real-time verification is performed based on preliminary flight plan data and preliminary real-time flight status data to obtain flight plan data and real-time flight status data, respectively.

3. The method according to claim 1, characterized in that, Step S2 is as follows: Flight features are extracted based on flight plan data and real-time flight status data to obtain flight feature data, which includes aircraft type feature data, flight mission data, flight time requirement data, and flight road surface data. Lighting demand baselines are set based on flight characteristic data to obtain lighting demand baseline data. The mission area is divided based on flight mission data and flight road surface data to obtain flight mission area data. Regional demand assessment is performed on flight mission area data to obtain flight mission area demand data. Weather condition data is obtained by acquiring weather condition data based on flight time requirements; Light intensity and adjustment range are set based on flight weather data, flight mission area demand data, and lighting demand baseline data to obtain lighting demand assessment data.

4. The method according to claim 1, characterized in that, The lighting simulation specifically includes: Navigation light source data is obtained by generating navigation light source data based on average brightness data and instantaneous anomaly data of navigation lights; Light radiation transmission data is obtained by analyzing the light source data and the light simulation model of the navigation lights. Based on the data of navigation light source and the simulation model of navigation light illumination, the interaction between the light source and the ground is analyzed to obtain data on the effect of light on the ground. Obtain measured illumination data; Based on the light radiation transmission data and the measured light data, deviation correction is performed to obtain the light radiation correction data. Obtain ground reflectivity measurement data; Based on the ground reflectivity measurement data and the data on the effect of sunlight on the ground, deviation correction is performed to obtain the corrected data on the effect of sunlight on the ground; Preliminary data on the irradiance range are obtained by fusing the data on the correction of solar radiation and the correction data on the effect of solar radiation on the ground.

5. The method according to claim 1, characterized in that, The node network construction is specifically as follows: Based on the navigation light node data, a node spatial network is constructed to obtain the first navigation light node network data. The communication topology network is constructed based on the navigation light node data to obtain the second navigation light node network data. The functional network is constructed based on the navigation light node data to obtain the third navigation light node network data. Based on the network data of the first navigation light node, the network data of the second navigation light node, and the network data of the third navigation light node, the node coordination relationship is processed to obtain the navigation light node network data.

6. The method according to claim 1, characterized in that, The calculation of remaining lighting resources is as follows: The remaining lighting power is calculated based on the remaining lighting resource data and the lighting implementation deviation data to obtain the remaining lighting power data; The remaining illumination range data is obtained by calculating the remaining illumination range based on the remaining lighting resource data and the lighting implementation deviation data. By integrating the remaining light power data and the remaining illumination range data, navigation light scheduling data is obtained.

7. The method according to claim 1, characterized in that, Step S4 is as follows: Based on flight plan data, mission area priorities are divided to obtain flight mission area priority data. Light control matching data is obtained by matching the flight mission area priority data and navigation light scheduling data. Based on the lighting control matching data and the navigation lighting scheduling data, the flight status adjustment area control is performed to obtain the navigation lighting system zonal control data, so as to carry out auxiliary operations for the management of the navigation lighting system based on power line carrier.

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