CN115451962A - Target tracking strategy planning method based on five-variable Carnot graph - Google Patents
Target tracking strategy planning method based on five-variable Carnot graph Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/66—Radar-tracking systems; Analogous systems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
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Abstract
The invention relates to a target tracking strategy planning method based on a five-variable Carnot diagram, which is characterized in that detection conditions of target track information and detection sensors at each point are processed, a calculation function based on the five-variable Carnot diagram is subjected to logic simplification is subjected to quick calculation, the working state of each sensor at each track point and the overall tracking state of a target are finally obtained, and a tracking strategy is planned. The invention has the following advantages: the tracking process can be divided according to the requirement of the tracking measurement task and a time axis, and comprises the links of waiting, capturing, tracking, recapturing and the like; decomposing the tracking tasks of all the sensors, and carrying out strategy setting by combining the working mode of the equipment and the planned aircraft track; the method for simplifying the working state calculation logic by the Carnot diagram reduces the operation amount, and has high accuracy and short operation time.
Description
Technical Field
The invention belongs to target tracking, and relates to a target tracking strategy planning method based on a five-variable Carnot graph.
Background
In practical situations, it is necessary to track various targets during the task by using various sensors, such as radar, optical devices, telemetry devices, etc. The tracking task has various targets, such as vehicles, aircrafts, missiles, reentry cabins and the like; and the situation is complex, and due to various environmental or artificial interference influences, the sensors may lose track of the target in the task. In addition, in the task of multiple targets and multiple sensors, the situation of tracking the target by each sensor is more complicated. In order to improve the tracking effect on the target, the sensors need to be reasonably scheduled in the task so as to efficiently utilize limited sensor resources. In order to better complete the task of target tracking, besides selecting a sensor with better performance and stronger anti-interference capability, what is more critical is how to use the sensor to track, namely the planning problem of the tracking strategy. The tracking strategy planning is the key for smoothly executing the tracking task, the good tracking strategy can predict the conditions of the sensors in the task process, reasonably arrange the scheduling and the use of the sensor resources, give full play to the performance advantages of each sensor to the maximum extent, ensure higher sensor coverage rate in the task process and obtain information advantages.
The existing tracking strategy planning technology can carry out certain theoretical estimation on the motion of a target, and can also carry out scheduling on sensor resources according to a certain tracking strategy which is estimated and planned. However, the prior art is less related to dividing the tracking process according to the whole time axis, and is less detailed to calculate the working state of the designated sensor to the designated target at the designated moment. If such detailed sensor information is to be obtained, it is often necessary to add code to the simulation to simulate at every point, which is computationally expensive and slow.
Disclosure of Invention
Technical problem to be solved
In order to avoid the defects of the prior art, the invention provides a target tracking strategy planning method based on a five-variable Carnot diagram, which is used for solving the problem that the working state of each sensor cannot be accurately and quickly calculated by the conventional tracking strategy planning method.
Technical scheme
A target tracking strategy planning method based on a five-variable Carnot graph is characterized by comprising the following steps:
step 1: reading the tracking state of the sensor in input according to time sequence in batches; the tracking state comprises the time, longitude and latitude and height of a track point, and whether each sensor detects a target;
step 2: according to the read data, the sensors comprise the latest 5 frames of data of the current frame, and a core method based on five-variable Carnot diagram simplified logic is adopted to calculate the overall tracking state of the target by any sensor at each moment:
current five frames satisfy
Beginning to enter recapture;
current five frames satisfy
Starting to enter capture;
otherwise, the tracking state is entered.
Wherein: ABCDE is the number of the detection tracking state of the sensor of 5 frames before the current frame according to the time sequence;
and continuously reading the next group of five frames of data, calculating the next working state of the batch, and repeating from the step 1 after the batch is finished to realize the tracking of the target.
The truth table of the core method based on the five-variable Carnot diagram simplified logic is as follows:
the working logic of the sensor is as follows:
when the sensor does not detect the target, the sensor is in a waiting state;
once a sensor detects a certain target, the sensor is switched to a capturing state of the target;
the sensor can not enter a tracking state when capturing a target in a first frame after being switched into a capturing state, but can enter the tracking state if capturing the target in a second frame or a third frame once; if the first frame is not captured, the second frame capture can also enable the sensor to enter the tracking; if the first frame and the second frame are not captured, the capturing state is exited and the recapture state is entered;
after the sensor enters a tracking state, if the target is lost, the sensor enters memory tracking; however, if two consecutive frames lose the target, the sensor enters a recapture state.
Advantageous effects
The invention provides a target tracking strategy planning method based on a five-variable Carnot graph, which is characterized in that detection conditions of target track information and detection sensors at each point are processed, a calculation function based on the five-variable Carnot graph is subjected to quick calculation after logic simplification, the working state of each sensor at each track point and the total tracking state of a target are finally obtained, and a tracking strategy is planned. The invention has the following advantages: the tracking process can be divided according to the requirement of the tracking measurement task and a time axis, and comprises the links of waiting, capturing, tracking, recapturing and the like; decomposing the tracking tasks of all the sensors, and carrying out strategy setting by combining the working mode of the equipment and the planned aircraft track; the method for simplifying the working state calculation logic by the Carnot diagram reduces the operation amount, and has high accuracy and short operation time.
Compared with the prior art, the invention has the following advantages:
the invention can utilize the detection condition of the sensors at each point to quickly divide the tracking process according to the detection logic of each sensor and the whole time axis, and can support the calculation of the single sensor or a specific target and derive detailed and accurate tracking strategy planning.
Aiming at a 5-order Markov process between an input detection state and an output working state, a calculation function is compiled through a five-variable Carnot diagram simplified calculation logic, so that multilayer complicated judgment sentences are avoided; even if the tracking states of all specific sensors to specific targets are required to be calculated in a multi-sensor multi-target task, the calculation can be completed within a short running time by calling the judgment function for multiple times, and the accuracy is guaranteed while the real-time performance is high.
Based on the thought of 5-order Markov process, the invention can correctly process any amount of data by a method of circularly rolling the data selection window, and can correctly derive a corresponding tracking strategy configuration scheme no matter only a few simple tracks or tracks with large data volume.
Drawings
FIG. 1 is a block diagram of a flow implementation of the present invention.
Fig. 2 is a truth table of sensor detection condition inputs and operating state outputs for the first 5 frames.
FIG. 3 is a Carnot diagram simplification concrete process and logical simplification result of the present invention.
FIG. 4 is a flow chart of the medium 5 order Markov algorithm of the present invention.
Fig. 5 is a schematic diagram of a test application applying the method to an overall system.
Detailed Description
The invention will now be further described with reference to the following examples and drawings:
reading the tracking states of the sensors in batches in a time sequence;
and counting the total data amount of the tracking state, and presetting a maximum batch kMax for the subsequent batch processing of the data.
Further, a variable k =0 is initialized to represent the batch number of the current data, so as to determine whether all data have been read.
Further, a batch of data is read in, the data amount i read in the batch is counted, and the purpose of recording is to judge whether the tail end of the input data is read at present or not, and to cope with a special case that the input data amount is very small.
Step two, reading the latest 5 frames according to the sensors and the overall working logic and the read-in data, calling a core calculation function based on five-variable Carnot diagram simplified logic, quickly calculating the sensors such as radar, optics and remote measurement at each moment and even the overall tracking state of the target, and rolling to the next frame for continuous calculation after the calculation is finished;
the judgment of the values of i and k is to process the special condition that traces in input data are very few, and needs to be independently judged; in general, an operating state calculation function based on a five-variable carnot diagram can be called for calculation.
The internal logic of this function is determined by the tracking logic of the sensor, as follows:
when the sensor does not detect the target, the sensor is in a waiting state;
once a sensor detects a certain target, the sensor is switched to a capturing state of the target;
the sensor captures a target in a first frame after being switched into a capturing state, and can not enable the target to enter a tracking state temporarily, but can enter the tracking state if the target is captured in a second frame or a third frame once; if the first frame is not captured, the second frame is captured, and the sensor can enter the tracking state; if the first frame and the second frame are not captured, the capturing state is exited and the recapture state is entered;
after the sensor enters the tracking state, if the target is lost, the sensor temporarily enters the memory tracking state; however, if two consecutive frames lose the target, the sensor enters a recapture state.
Further, according to the logic, it may be determined that the relationship between the tracking status and the operating state of the sensor is a 5-step Markov process. I.e., tracking conditions 6 frames ago and earlier, cannot have an effect on the current operating state, and if only the first 4 frames or less are considered, the current operating state cannot be accurately calculated.
The detection conditions of the sensors of the previous 5 frames are numbered as logic variables ABCDE from time to time (1 is successfully selected, 0 is failed), and the values and the output working states have certain logic relations, and the relations can be described by a truth table of FIG. 2. But if the logic is applied without processing simplification, a cumbersome number of judgments are required. The invention thus logically simplifies, as shown in fig. 3, by means of a five variable carnot diagram. The final results were as follows:
after the computation of the working states of the sensors and the overall tracking state on the trace point is completed, as shown in fig. 4, the computation process of 5-step markov is continued, i.e. the window is scrolled by one frame, and the data of the latest 5 frames are updated, so as to compute the working state in the next frame.
And step three, exporting the calculated data of the batch to finally obtain a tracking strategy output configuration scheme.
After the calculation of the batch is completed, the calculation result of the batch data is added into an output configuration scheme of the tracking strategy; meanwhile, the data of the batch is temporarily backed up for calling when the working state of the trace point of the next batch is calculated. And when k is not satisfied with kMax, the calculation of all data is completed, and a final output tracking strategy configuration scheme is obtained. The configuration scheme comprises detailed information of tracking working states of the sensors on the targets at each trace, and can provide reference for tracking tasks.
Fig. 5 is a schematic diagram of the test use of this method. The use of the tracking strategy planning method is that after the superior module calculates according to the target track, the tracking path and the sensor information, the input data required by the tracking strategy planning module shown in table 1 is obtained, and the tracking strategy output configuration scheme shown in table 2 can be derived from the tracking strategy planning module.
Table 1 input tracking status data example
Table 2 output configuration scheme example
The above description is only exemplary of the present invention and should not be taken as limiting the invention, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. A target tracking strategy planning method based on a five-variable Carnot graph is characterized by comprising the following steps:
step 1: reading the tracking state of the sensor in input according to time sequence in batches; the tracking state comprises the time, longitude and latitude and height of a track point, and whether each sensor detects a target;
step 2: according to the read data, the sensors comprise the latest 5 frames of data of the current frame, and a core method based on five-variable Carnot diagram simplified logic is adopted to calculate the overall tracking state of the target by any sensor at each moment:
current five frames satisfy
Beginning to enter recapture;
current five frames satisfy
Starting to enter capture;
otherwise, the tracking state is entered.
Wherein: ABCDE is the number of the detection tracking state of the sensor of 5 frames before the current frame according to the time sequence;
and continuously reading the next group of five frames of data, calculating the next working state of the batch, and repeating from the step 1 after the batch is finished to realize the tracking of the target.
2. The five-variable carnot diagram based target tracking strategy planning method of claim 1, characterized in that: the truth table of the core method based on the five-variable Carnot diagram simplified logic is as follows:
3. the five-variable carnot diagram based target tracking strategy planning method of claim 1, characterized in that:
the working logic of the sensor is as follows:
when the sensor does not detect the target, the sensor is in a waiting state;
once a sensor detects a certain target, the sensor is switched to a capturing state of the target;
the sensor captures a target in a first frame after being switched into a capturing state, and can not enable the target to enter a tracking state temporarily, but can enter the tracking state if the target is captured in a second frame or a third frame once; if the first frame is not captured, the second frame capture can also enable the sensor to enter the tracking; if the first frame and the second frame are not captured, the capturing state is exited and the recapture state is entered;
after the sensor enters a tracking state, if the target is lost, the sensor enters memory tracking; however, if two consecutive frames lose the target, the sensor enters a recapture state.
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