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

Abstract

The application relates to a multi-target simulation method for a communication and perception integrated joint monitoring scene, comprising the following steps: constructing a communication and perception integrated joint monitoring system comprising multiple sensors; planning a networking layout of the joint monitoring system, simulating station positions of the sensors based on the networking layout, and establishing a decision factor matrix of each sensor to simulate a joint monitoring process of the sensors; planning activity events of each monitoring target and different types of interference sources based on a set time domain T, and obtaining several event scripts; loading a corresponding event script according to a set target simulation scheme; based on the networking layout and the loaded event script, calculating monitoring result data sequences of each monitoring target and interference source, and distributing the monitoring result data sequences to each sensor. The application can provide verification data sources for a communication and perception integrated system to jointly monitor a multi-target scene, thereby reducing system scheme demonstration time, equipment investment and technical risks.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication and perception integration, in particular to a joint monitoring scene multi-target simulation method of a communication and perception integration system. BACKGROUND

[0002] When deploying a communication and perception integration network for joint monitoring of multiple targets, especially in the scene of collaborative monitoring of "low, slow and small" targets by multiple sensors, sufficient simulation testing and data verification are required. The existing technology lacks a simulation scheme specifically for this application scenario. SUMMARY

[0003] The technical problem to be solved by the present application is to provide a joint monitoring scene multi-target simulation method of a communication and perception integration system, which can provide verification data sources for the joint monitoring scene of multiple targets by a communication and perception integration system.

[0004] The technical solution adopted by the present application to solve the technical problem is to provide a joint monitoring scene multi-target simulation method of a communication and perception integration system, comprising the following steps:

[0005] Constructing a joint monitoring system of a communication and perception integration including multiple sensors;

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

[0007] Based on a set time domain T, planning the activity events of each monitoring target and different types of interference sources, and obtaining several event scripts;

[0008] Loading the corresponding event script according to the set target simulation scheme;

[0009] Based on the networking layout and the loaded event script, the monitoring result data sequence of each monitoring target and interference source at each time is calculated and distributed to each sensor.

[0010] Further, the planning of the networking layout of the joint monitoring system and the simulation of the station positions of each sensor based on the networking layout comprises:

[0011] If the joint monitoring system only contains one monitoring subnet, the station positions of each sensor are simulated so that the geometric dilution of precision factor of the monitoring subnet meets the set requirement;

[0012] If the joint monitoring system is a multi-subnet collaborative networking, the subnet layout is planned according to the set subnet grouping constraint, and the station positions of each sensor in the monitoring subnet are simulated so that the geometric dilution of precision factor of each monitoring subnet meets the set requirement.

[0013] Furthermore, the subnet layout is dynamically adjusted according to the time domain T, and in each monitoring subnet, only one sensor acts as a signal transmitter at any given time, while the other sensors act as signal receivers.

[0014] Furthermore, the event script is a structured description script of the activity events of the monitored 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 monitored target's number, starting position, ending position, movement stage, running direction, running speed and running acceleration.

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

[0017] Furthermore, the activity events of the interference source are planned using the following methods:

[0018] For the first interference source, its activity area, activity route and motion attributes are planned. The motion attributes include the number of the first interference source, the starting position, the ending position, the motion stage, the running direction, the running speed and the running acceleration.

[0019] For the second interference source, its activity area is planned, and its location, time phase, duration, and frequency of occurrence within the activity area are set using multiple random methods;

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

[0021] For the fourth interference source, the accompanying area, location, frequency, time period, encounter method, and duration of the false target are randomly generated based on the real target's trajectory.

[0022] Furthermore, based on the network layout and loaded event scripts, the monitoring result data sequence of each monitoring target and interference source at each time moment is calculated, 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 positions of each monitoring target at each time are determined, and then according to the working position and working attribute of the sensor at the time, the signal propagation path of each sensor relative to the target is determined, the received signal data of each sensor for the detection target is calculated, and the monitoring result data sequence is obtained;

[0025] According to the loaded event script, the real positions of each interference source at each time are determined, and then according to the working position and working attribute of the sensor at the time, the signal propagation path of each sensor relative to the interference source is determined, the received signal data of each sensor for the interference source is calculated, and the obtained interference data is interpolated in the monitoring result data sequence.

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

[0027] Further, the decision factor matrix includes the deployment position of the sensor, the effective action distance, the effective coverage angle, the working scene for the area, the sensor transceiver relationship switching beat, and the data acquisition frequency.

[0028] Advantages

[0029] Compared with the prior art, the present application has the following advantages and positive effects: by constructing a communication and perception integrated joint monitoring simulation system, planning the networking layout, and monitoring the activity events of the target and the interference source, and structurally describing the activity events in the form of scripts, according to different target simulation schemes, loading corresponding event scripts, and using data simulation according to existing standards, the present application provides a deployment flexible, scene fully covered, environment electromagnetic feature complete (including clutter and interference signal), target feature cleaning expression and controllable verification data source for the whole system perception target, thereby reducing the system scheme demonstration time, equipment investment, and clarifying the technical risk. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 is a flowchart of an embodiment of the present application;

[0031] Figure 2 is a communication and perception integrated joint monitoring scene schematic diagram of an embodiment of the present application. DETAILED DESCRIPTION

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

[0033] Embodiments of the present application relate to a communication and perception integrated joint monitoring scene multi-target simulation method, as shown in the following steps: Figure 1

[0034] 1) Simulation scene planning

[0035] 2) Multi-target 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) Simulation data distribution

[0041] The above steps will be described in detail below in combination with a simulation application scenario.

[0042] The present embodiment adopts a typical communication system and integrates a radar perception function module to complete the perception monitoring of low-altitude, slow-speed small targets under the condition constraints of time scale, frequency, space, and power. As shown in the following steps: Figure 2 The simulated multi-targets are the targets for monitoring in the real application scenario, the multi-station cooperative networking scene in the real working environment is simulated, the multi-sensor is planned to participate in the monitoring network in a timely manner in the form of a script, the task subnetwork for different monitoring areas is formed, and only one sensor is the signal sending end at the same time in each task subnetwork (at a certain time), and the remaining sensors are all signal receiving ends.

[0043] The present embodiment takes a unified theoretical time scale (data time scale) as the monitoring result mounting carrier, a multi-sensor beat unified calibration source, a data generation time sequence calibration index source, and a data synchronization time sequence marking source. The sensor participates in the monitoring network in a timely manner according to the script setting, and the sensors in the formed network switch roles to emit signals at a given time, and receive signals at the remaining time.

[0044] 1) Simulation scene planning

[0045] The simulation scene of the present application includes a multi-sensor single network scene and a multi-sensor cooperative networking multi-subnetwork scene.

[0046] Single network scene: based on the geographical position networking configuration of N (sending, N-1 receiving) sensors, the sensor networking layout is planned according to system requirements, and the target monitoring geometric precision factor is calculated according to the sensor layout (based on the algorithm:

[0047] ​GDOP), and then complete the guidance of the system simulation sensor deployment station; at the same time, the system needs to establish a decision factor matrix for the deployment position, effective action distance, effective coverage angle, working scene area, sensor transceiver relationship switching rhythm, data acquisition frequency and other factors of each sensor.

[0048] The collaborative networking multi-subnet scenario is: based on the geographical location networking configuration of N (transmission, N-1 reception) sensors, first plan the system subnet grouping constraint (M, the upper and lower limits of the target monitoring site), plan the sensor subnet layout based on the time domain (T, including several time points) according to the system requirements, the scene contains multiple subnets, and the subnets are dynamically adjusted in real time according to the time domain T, and the planning in a single subnet is carried out according to the above "single network scenario".

[0049] 2) Multi-objective planning

[0050] The multi-target activity planning supports the development of map control 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 the full description of multi-target activities in each time domain. Based on the time domain T, single or batch processing is used to plan multi-target activity areas, routes, and target activity attributes, including: start and end positions, target numbers and motion stages, target running direction, speed, acceleration, etc.

[0051] 3) Interference source planning:

[0052] In order to fully simulate the real scene, the interference source is divided into real target side virtual image interference data source, fixed point, fixed track and regional random position interference source and other multi-type data 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, use multiple random methods to determine the position, time stage, duration (duration of interference source stage appearance), interference source appearance frequency and other factors of the interference source in the area; for fixed track target execution mode as described in "target planning", limit the activity duration and plan the appearance frequency, time stage and other factors; for random false targets, refer to the false target index, generate false targets by randomly generating false target appearance area, frequency, time period, duration period and other factors; for "companion" false targets, generate false target accompanying area according to the real target track, appearance place, frequency, time period, meeting mode, duration period and other related factors;

[0053] 4) Target simulation data generation:

[0054] On the basis of step 1) and step 2), the data slice collection of multi-target based on time domain T is completed according to the plan (the data slice is the set of positions of each target at the same time), and the data slice collection beat is greater than or equal to the multi-station joint data accumulation distribution beat. Among them, according to the real-time position of the sensor deployment, the role conversion matrix of the receiving and transmitting relationship, and the target motion attribute data in the multi-target activity event, as well as the data slice time sequence, the real position of the target at the fixed point is determined first, and then the propagation distance of the "signal receiving and transmitting pair" of different station sensors relative to the target is calculated, and according to the signal propagation path, the monitoring time difference, distance, Doppler and other result data obtained by converting the received signal of each sensor are calculated, and the signal strength, signal correction source, Doppler change value and other data are calculated according to the planned target attribute.

[0055] 5) Interference source simulation data generation:

[0056] On the basis of step 1) and step 3), the plan is completed, that is, the factors such as the appearance area, frequency, time period, duration of the interference source and the interference strength are determined. The interference source is theoretically equivalent to the generation method of target simulation data in the simulation data calculation process, so the time-domain-based interference source data point sequence calculation completely adopts the target simulation calculation process; the generated interference data is interpolated in the multi-target monitoring result data sequence (based on time domain).

[0057] 6) Simulation data buffering and loading:

[0058] The simulation data buffering is divided into two types: one is the structured description of the target activity event and the interference source activity event based on time domain (referred to as scenario); the other is the feature and time domain monitoring result data generated for each sensor based on the scenario, step 4) and step 5). The nominal time scale (unified theoretical time scale) is used for data simulation driving in this embodiment, that is, it is separated from the actual time line, the time scale is used as the carrier of the simulation target and the interference source activity event, and the simulation target and the interference source activity event are used as structured data. Different structured data corresponding to different activity events can be recorded as different simulation scenarios to facilitate rapid simulation scheme. Different simulation scenarios can be loaded according to the demand in the data simulation process, and different simulation scenarios can generate corresponding monitoring result data according to the real-time deployment of each sensor. In the data buffering and data file, the simulation rhythm can be controlled to continuously cycle and parallel data distribution in the case of scene repetition.

[0059] 7) Simulation data distribution:

[0060] Because of the different deployment of each sensor, the data distribution to each sensor needs to be completed based on the real-time deployment change matrix to simulate the target monitoring solution. Before data distribution, the data style is connected by using the adaptation mode (planning customization) to facilitate flexible connection, and the monitoring result data of each sampling processing is distributed to each sensor in each time task subnetwork according to the time domain matrix.

Claims

1. A method for multi-target simulation of communication and sensing integrated joint monitoring scenarios, characterized in that, The method comprises the following steps: constructing a communication and perception integrated joint monitoring system comprising a plurality of sensors; planning a networking layout of the joint monitoring system, simulating deployment of station positions of the sensors based on the networking layout, and establishing a decision factor matrix of the sensors to simulate a joint monitoring process of the sensors; planning activity events of each monitoring target and different types of interference sources based on a set time domain T, obtaining a plurality of event scripts which are structured description scripts of the activity events of the monitoring targets and / or the interference sources based on the time domain T; loading a corresponding event script according to a set target simulation scheme; based on the networking layout and the loaded event script, calculating monitoring result data sequences of each monitoring target and interference source at each time, and distributing the monitoring result data sequences to each sensor; the calculation of the monitoring result data sequences of each monitoring target and interference source at each time based on the networking layout and the loaded event script comprises: obtaining a working position and a working attribute of the sensor at the current time based on the networking layout; determining real positions of each monitoring target at each time according to the loaded event script, and then determining signal propagation paths of each sensor relative to the target according to the working position and the working attribute of the sensor at the time, calculating received signal data of each sensor for the detection target, and obtaining the monitoring result data sequences; determining real positions of each interference source at each time according to the loaded event script, and then determining signal propagation paths of each sensor relative to the interference source according to the working position and the working attribute of the sensor at the time, calculating received signal data of each sensor for the interference source, and interpolating the obtained interference data into the monitoring result data sequences.

2. The method of claim 1, wherein, The planning of the networking layout of the joint monitoring system and the simulation of the deployment of the station positions of the sensors based on the networking layout comprises: if the joint monitoring system only comprises one monitoring subnetwork, simulating the deployment of the station positions of the sensors so that a geometric dilution of precision factor of the monitoring subnetwork meets a set requirement; if the joint monitoring system is a multi-subnetwork cooperative networking, planning a subnetwork layout according to a set subnetwork grouping constraint, and simulating the deployment of the station positions of the sensors in the monitoring subnetwork so that the geometric dilution of precision factor of each monitoring subnetwork meets the set requirement.

3. The method of claim 2, wherein, The subnetwork layout is dynamically adjusted according to the time domain T, and only one sensor in each monitoring subnetwork acts as a signal sending end at the same time, and the remaining sensors act as signal receiving ends.

4. The method of claim 1, wherein, The activity events of the monitoring target comprise an activity area, an activity route and motion attributes of the monitoring target, and the motion attributes comprise a number, a starting position, a terminal position, a motion stage, a running direction, a running speed and a running acceleration of the monitoring target.

5. The method of claim 1, wherein, The different types of interference sources comprise a first interference source moving along a set flight path, a second interference source randomly generated in a determined area, a third interference source randomly generated in an undetermined area, and a fourth interference source accompanying the sensor.

6. The method of claim 5, wherein, The activity events of the interference sources are planned by the following method: The activity region, activity route and motion attribute of the first interference source are planned, and the motion attribute includes the number, starting position, ending position, motion stage, running direction, running speed and running acceleration of the first interference source; The activity region of the second interference source is planned, and the position, time stage, duration and frequency of occurrence of the second interference source in the activity region are set in a multi-time random manner; The region, frequency, time stage and duration of occurrence of the third interference source are set in a multi-time random manner; The accompanying region, occurrence location, occurrence frequency, occurrence time period, meeting mode and duration of the false target are randomly generated according to the real target track for the fourth interference source.

7. The method of claim 1, wherein, The received signal data includes the monitoring time difference, distance, transmission delay, signal strength, signal correction source, Doppler value and Doppler change value.

8. The method of claim 1, wherein, The decision factor matrix includes the deployment position, effective action distance, effective coverage angle, working scene for the region, sensor transceiver relationship switching beat and data acquisition frequency of the sensor.

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