Communication perception integrated system joint monitoring scene multi-target simulation method

Abstract

The invention relates to a multi-target simulation method for a communication and perception integrated combined monitoring scene. The method comprises the following steps: constructing a communication and perception integrated combined monitoring system comprising a plurality of sensors; planning a networking layout of the combined monitoring system, simulating and deploying a station of each sensor based on the networking layout, and establishing a decision factor matrix of each sensor to simulate a combined monitoring process of the sensors; based on a set time domain T, planning activity events of each monitoring target and different types of interference sources, and obtaining a plurality of event scripts; loading a corresponding event script according to a set target simulation scheme; and based on the networking layout and the loaded event script, calculating a monitoring result data sequence of each monitoring target and interference source, and distributing the monitoring result data sequence to each sensor. According to the invention, a verification data source can be provided for a multi-target joint monitoring scene of a communication perception integrated system, so that the scheme demonstration time and equipment investment of the whole system are reduced, and the technical risk is clarified.

Description

Technical Field

[0001] The present invention relates to the technical field of communication perception integration, and in particular to a multi-target simulation method for a joint monitoring scenario of a communication perception integration system. Background Art

[0002] When deploying a communication-sensing integrated network for multi-target joint monitoring, sufficient simulation testing and data verification are required, especially in scenarios where multiple sensors are used to complete collaborative monitoring of "low, slow, and small" targets. The existing technology lacks a simulation solution specifically for this application scenario. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a multi-target simulation method for a joint monitoring scenario of a communication perception integrated system, which can provide a verification data source for the joint monitoring scenario of multiple targets by the communication perception integrated system.

[0004] The technical solution adopted by the present invention to solve the technical problem is: to provide a multi-target simulation method for a communication perception integrated joint monitoring scenario, comprising the following steps:

[0005] Build a communication-sensing integrated joint monitoring system including multiple sensors;

[0006] Planning the network layout of the joint monitoring system, simulating the deployment of each sensor station based on the network layout, and establishing a decision factor matrix of each sensor to simulate the joint monitoring process of the sensors;

[0007] Based on the set time domain T, plan the activity events of each monitoring target and different types of interference sources to obtain several event scenarios;

[0008] Load the corresponding event script according to the set target simulation plan;

[0009] Based on the network layout and loaded event scripts, the monitoring result data sequence of each monitoring target and interference source at each moment is solved and distributed to each sensor.

[0010] Furthermore, the planning of the network layout of the joint monitoring system and the simulation of the deployment of the positions of each sensor based on the network layout include:

[0011] If the joint monitoring system only includes one monitoring subnet, the deployment positions of each sensor are simulated so that the geometric precision factor of the monitoring subnet meets the set requirements;

[0012] If the joint monitoring system is a multi-subnet collaborative network, the subnet layout is planned according to the set subnet grouping constraints, and the positions of each sensor in the monitoring subnet are deployed in a simulated manner so that the geometric precision factor of each monitoring subnet meets the set requirements.

[0013] Furthermore, the subnet layout is dynamically adjusted according to the time domain T, and in each monitoring subnet, only one sensor is used as a signal sending end at the same time, and the remaining sensors are used as signal receiving ends.

[0014] Furthermore, the event script is a structured description script of the activity events of the monitoring target and / or interference source based on the time domain T.

[0015] Furthermore, the activity events of the monitored target include the activity area, activity route and motion attributes of the monitored target, and the motion attributes include the number, starting position, ending position, motion stage, running direction, running speed, and running acceleration of the monitored target.

[0016] Furthermore, the different types of interference sources include a first interference source that moves along a set track, a second interference source that is randomly generated in a determined area, a third interference source that is randomly generated in an uncertain area, and a fourth interference source that accompanies the sensor.

[0017] Furthermore, the activity events of interference sources are planned by the following methods:

[0018] For the first interference source, plan its activity area, activity route and motion attributes, wherein the motion attributes include the number, starting position, ending position, motion stage, running direction, running speed, and running acceleration of the first interference source;

[0019] For the second interference source, plan its activity area, and set its location, time stage, duration, and frequency of occurrence in the activity area in a random manner for multiple times;

[0020] For the third interference source, the area, frequency, time stage, and duration of its occurrence are set in a random manner multiple times;

[0021] For the fourth interference source, the accompanying area, appearance location, appearance frequency, appearance time period, encounter mode, and duration of the false target are randomly generated according to the real target track.

[0022] Furthermore, the monitoring result data sequence of each monitoring target and interference source at each moment is calculated based on the network layout and the loaded event script, including:

[0023] Based on the network layout, obtain the current working position and working attributes of the sensor;

[0024] According to the loaded event script, the real position of each monitoring target at each moment is determined, and then according to the working position and working properties of the sensor at that moment, the signal propagation path of each sensor relative to the target is determined, and the receiving signal data of each sensor for the detection target is solved to obtain the monitoring result data sequence;

[0025] According to the loaded event script, the actual position of each interference source at each moment is determined, and then the signal propagation path of each sensor relative to the interference source is determined according to the working position and working properties of the sensor at that moment, and the received signal data of each sensor for the interference source is solved, and the obtained interference data is interpolated into the monitoring result data sequence.

[0026] Furthermore, the received signal data includes monitoring time difference, distance, transmission delay, signal strength, signal correction source, Doppler value, and Doppler change value.

[0027] Furthermore, the decision factor matrix includes the deployment location of the sensor, the effective action distance, the effective coverage angle, the working scene target area, the switching rhythm of the sensor transmission and reception relationship, and the data collection frequency.

[0028] Beneficial Effects

[0029] Due to the adoption of the above-mentioned technical scheme, the present invention has the following advantages and positive effects compared with the prior art: the present invention constructs a communication perception integrated joint monitoring simulation system, plans its networking layout, and monitors the activity events of targets and interference sources, and describes the activity events in a structured form of scripts, loads corresponding event scripts according to different target simulation schemes, and uses data simulation methods according to existing standards to provide the entire system with a verification data source with flexible deployment, sufficient scene coverage, complete environmental electromagnetic characteristics (including clutter and interference signals), clean expression of target characteristics, and controllable, thereby reducing the system solution demonstration time, equipment investment, and clarifying technical risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is a flow chart of an embodiment of the present invention;

[0031] Figure 2 It is a schematic diagram of a communication-aware integrated joint monitoring scenario according to an implementation mode of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0033] The embodiments of the present invention relate to a multi-target simulation method for a communication-sensing integrated joint monitoring scenario, such as Figure 1 As shown, the following steps are included:

[0034] 1) Simulation scenario planning

[0035] 2) Multi-objective planning

[0036] 3) Target simulation data generation

[0037] 4) Real-time interference source planning

[0038] 5) Interference source simulation data generation

[0039] 6) Simulation data buffering and loading

[0040] 7) Simulate data distribution

[0041] The above steps are explained in detail below with reference to simulated application scenarios.

[0042] This implementation adopts a typical communication system and integrated radar sensing function module to complete the sensing and monitoring of low-altitude, slow-moving small targets under the constraints of time scale, frequency, airspace, power and other conditions. Figure 2 As shown in the figure, the simulated multi-targets are the monitoring targets in real application scenarios, simulating the multi-station collaborative networking scenario in a real working environment. The script form is used to plan multiple sensors to participate in the monitoring network in a timely manner to form task subnets for different monitoring areas. In each task subnet (determined at a fixed time), only one sensor is the signal transmitter at the same time, and the rest of the sensors are signal receivers.

[0043] This implementation uses a unified theoretical time scale (data time scale) as a monitoring result mounting carrier, a unified calibration source for multiple sensor beats, a data generation timing calibration indicator source, and a data synchronization timing mark source. Sensors participate in the monitoring network in a timely manner according to the script settings. The sensors in the network transmit signals at a given time according to the role switching scheme, and receive signals at other times.

[0044] 1) Simulation scenario planning

[0045] The present invention targets field simulation scenarios including multi-sensor single network scenarios and multi-sensor collaborative networking multi-subnet scenarios.

[0046] Single network scenario: Based on the geographic location networking configuration of N (sending, N-1 receiving) sensors, the sensor network layout is planned according to system requirements, and the target monitoring geometric precision factor calculation is completed according to the sensor layout (based on the algorithm:

[0047] GDOP), and then complete the guidance of the deployment position of the system simulation sensors; at the same time, the system needs to establish a decision factor matrix for factors such as the deployment position of each sensor, effective action distance, effective coverage angle, working scene target area, sensor transmission and reception relationship switching rhythm, and data collection frequency.

[0048] The collaborative networking multi-subnet scenario is: based on the geographic location networking configuration of N (sending, N-1 receiving) sensors, first plan the system subnet grouping constraints (M, the upper and lower limits of the sites required for target monitoring), and plan the sensor subnet layout based on the time domain (T, including several moments) according to system requirements. The scenario contains multiple subnets, and the subnets are adjusted in real time according to the time domain T. The planning within a single subnet is carried out according to the above "single network scenario".

[0049] 2) Multi-objective planning

[0050] Multi-target activity planning supports the development of map controls based on open source resources to control the formation of multi-target activity point tracks and related motion attribute changes, and also supports the use of scripts to structure and fully describe multi-target activity events in each time domain. Based on the time domain T, single or batch processing plans for multi-target activity areas and routes, and at the same time plans target activity attributes, including: starting and ending positions, target numbers and motion stages, target running directions, speeds, accelerations and other attributes.

[0051] 3) Interference source planning:

[0052] In order to fully simulate the real scene, the interference sources are divided into multiple data interference sources such as the real target side virtual image interference data source, fixed point, fixed track and regional random position interference sources. Different types of interference sources use different interference source planning schemes: For fixed track and regional random interference sources, first plan the interference source activity area, and use multiple random methods to determine the location, time stage, duration (duration of the interference source stage), frequency of interference source occurrence and other factors of the interference source in the area; For the fixed track target, the execution method is as described in "target planning", limiting its activity duration, and planning the frequency of occurrence, time stage and other factors; For random false targets, refer to the false target indicators, and randomly generate the false target appearance area, frequency, time period, duration period and other factors; For "accompanying" false targets, randomly generate the accompanying area of ​​the false target according to the real target track, and the relevant factors such as the appearance location, frequency, time period, encounter method, duration period, etc.

[0053] 4) Target simulation data generation:

[0054] On the basis of step 1) and step 2), the data slice collection of multiple targets based on the time domain T is completed according to the plan (data slice is the collection of the positions of each target at the same time), and the data slice collection beat is greater than or equal to the cumulative distribution beat of the multi-station joint data. Among them, the data slice is based on the real-time position of the sensor deployment, the role conversion matrix of the receiving and sending relationship, the target motion attribute data in the multi-target activity event, and the data slice time series. First, the real position of the target at the fixed point is determined, and then the propagation distance of the "signal receiving and sending pair" of sensors at different sites relative to the target is calculated. According to the signal propagation path, the solution is converted into the result data obtained by the receiving signal of each sensor itself: monitoring time difference, distance, Doppler, etc., and the corresponding transmission delay time calculation is completed at the same time. According to the planned target attributes, the signal strength, signal correction source, Doppler change value and other data are solved.

[0055] 5) Interference source simulation data generation:

[0056] On the basis of step 1) and step 3), the planning is completed, and the factors such as the interference source occurrence area, frequency, time period, duration period, and interference intensity and other attributes have been determined. The simulation data solution process of the interference source is theoretically equivalent to the generation method of the target simulation data. Therefore, the solution of the interference source data point sequence based on the time domain completely adopts the target simulation solution process; the generated interference data is interpolated in the multi-target monitoring result data sequence (based on the time domain).

[0057] 6) Simulation data buffering and loading:

[0058] There are two types of simulation data buffers: one is a structured description of target activity events and interference source activity events based on the time domain (called a script); the other is the feature and time domain monitoring result data for each sensor generated based on the script through steps 4) and 5). This implementation method uses a nominal time scale (a unified theoretical time scale) as the data simulation driver, that is, it is separated from the actual timeline. The time scale is used as a carrier of simulation target and interference source activity events, and the simulation target and interference source activity events are used as structured data. The structured data corresponding to different activity events can be recorded as different simulation scripts to facilitate the rapid formation of simulation plans. Different simulation scripts can be loaded according to demand during the data simulation process. Different simulation scripts can be used to generate corresponding monitoring result data based on the real-time deployment of each sensor. In the data buffer and data file, the simulation rhythm can be controlled to continuously cycle and distribute parallel data when the scene is repeated.

[0059] 7) Simulation data distribution:

[0060] Since the deployment of each sensor is different, it is necessary to complete the data distribution of the simulated target monitoring solution to each sensor based on the real-time deployment change matrix. Before data distribution, the adaptation mode (planning customization) is used to complete the data style docking for flexible docking, and the sampling and processed monitoring result data is distributed to each sensor in the task subnet at each moment according to the time domain matrix.

Claims

1. A multi-target simulation method for a communication-aware integrated joint monitoring scenario, characterized in that: The following steps are involved: Build a communication-sensing integrated joint monitoring system including multiple sensors; Planning the network layout of the joint monitoring system, simulating the deployment of each sensor station based on the network layout, and establishing a decision factor matrix of each sensor to simulate the joint monitoring process of the sensors; Based on the set time domain T, plan the activity events of each monitoring target and different types of interference sources to obtain several event scenarios; Load the corresponding event script according to the set target simulation plan; Based on the network layout and loaded event scripts, the monitoring result data sequence of each monitoring target and interference source at each moment is solved and distributed to each sensor.

2. The method according to claim 1, characterized in that The planning of the network layout of the joint monitoring system and the simulation of the deployment of the positions of each sensor based on the network layout include: If the joint monitoring system only includes one monitoring subnet, the deployment positions of each sensor are simulated so that the geometric precision factor of the monitoring subnet meets the set requirements; If the joint monitoring system is a multi-subnet collaborative network, the subnet layout is planned according to the set subnet grouping constraints, and the positions of each sensor in the monitoring subnet are deployed in a simulated manner so that the geometric precision factor of each monitoring subnet meets the set requirements.

3. The method according to claim 2, characterized in that The subnet layout is dynamically adjusted according to the time domain T, and in each monitoring subnet, only one sensor is used as a signal sending end at the same time, and the remaining sensors are used as signal receiving ends.

4. The method according to claim 3, characterized in that The event script is a structured description script of the activity events of the monitoring target and / or interference source based on the time domain T.

5. The method according to claim 1, characterized in that The activity events of the monitored target include the activity area, activity route and motion attributes of the monitored target, and the motion attributes include the number, starting position, ending position, motion stage, running direction, running speed, and running acceleration of the monitored target.

6. The method according to claim 1, characterized in that The different types of interference sources include a first interference source that moves along a set track, a second interference source that is randomly generated in a determined area, a third interference source that is randomly generated in an uncertain area, and a fourth interference source that accompanies the sensor.

7. The method according to claim 1, characterized in that The activity events of the interference source are planned by the following method: for the first interference source, its activity area, activity route and motion attributes are planned, and the motion attributes include the number, starting position, end position, motion stage, running direction, running speed, and running acceleration of the first interference source; For the second interference source, plan its activity area, and set its location, time stage, duration, and frequency of occurrence in the activity area in a random manner for multiple times; For the third interference source, the area, frequency, time stage, and duration of its occurrence are set in a random manner multiple times; For the fourth interference source, the accompanying area, appearance location, appearance frequency, appearance time period, encounter mode, and duration of the false target are randomly generated according to the real target track.

8. The method according to claim 1, characterized in that The monitoring result data sequence of each monitoring target and interference source at each moment is calculated based on the network layout and the loaded event script, including: Based on the network layout, obtain the current working position and working attributes of the sensor; According to the loaded event script, the real position of each monitoring target at each moment is determined, and then according to the working position and working properties of the sensor at that moment, the signal propagation path of each sensor relative to the target is determined, and the receiving signal data of each sensor for the detection target is solved to obtain the monitoring result data sequence; According to the loaded event script, the actual position of each interference source at each moment is determined, and then the signal propagation path of each sensor relative to the interference source is determined according to the working position and working properties of the sensor at that moment, and the received signal data of each sensor for the interference source is solved, and the obtained interference data is interpolated into the monitoring result data sequence.

9. The method according to claim 8, characterized in that The received signal data includes monitoring time difference, distance, transmission delay, signal strength, signal correction source, Doppler value, and Doppler change value.

10. The method according to claim 1, characterized in that The decision factor matrix includes the deployment location of the sensor, the effective range, the effective coverage angle, the working scene target area, the switching rhythm of the sensor transmission and reception relationship, and the data collection frequency.

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