JP2000284050A - Track predicting processor, track prediction processing method and aircraft supervisory system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To predict a track up to a long-time future at a high accuracy. SOLUTION: A track predicting processor 5 comprises a setting unit 11 for setting the sampling number for use in prediction of the track, and a track predicting processor unit 12 for predicting the track by calculations, using flying position information of the set sampling number, thereby predicting the track in an n-th scan future. The setting unit 11 increases the sampling number to be set as the predicting time becomes long in future. The sampling number to be set may be increased with increase of the error based on past actual results.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

TECHNICAL FIELD The present invention relates to a wake prediction processing device,
The present invention relates to a method and an aircraft monitoring system, and more particularly to improving the accuracy of wake prediction.

[0002]

2. Description of the Related Art When considering the flight of an aircraft as a motion model, the track may suddenly change due to sudden turning or suddenly being affected by wind at a certain point. Impossible. However, the system or the like cannot actually cope with a sudden change (drift) in the flight position, and the possibility of an accident or the like occurring in such a situation increases. Therefore, even when such drift occurs, it is desired to predict the wake after drift has occurred as accurately as possible.

Conventionally, a least-squares method or the like is used as a method for predicting a wake. Generally, a tracking processing device mounted on an aircraft monitoring system performs tracking of each aircraft by detecting a flight position of the aircraft every time the radar scans at a predetermined time interval. Gain a wake by connecting each aircraft. However, actually, since the detected value includes a measurement error or the like that cannot be completely removed, it is necessary to smooth the wake by the detected value.
The least squares method is used as one method for performing this smoothing. In the least-squares method, a wake is obtained based on flight positions detected by aircraft in the past several times. Then, at the time of the next scan, it can be predicted that the aircraft will appear on the line of the obtained wake. By referring to the flight speed and the like, it is possible to predict the flight position at a point one scan ahead at a pinpoint. It can be said that improving the accuracy of predicting the flight position at the time point one scan ahead is equivalent to improving the accuracy of the wake. In the tracking processing, a bin for tracking is set with reference to the predicted flight position, and an aircraft appearing in the area of the bin is identified as an aircraft for which a wake is to be obtained.

[0004] When linear regression is performed in general motion analysis, it is considered that the prediction becomes closer to the reality as the number of past performance data (detected flight positions) increases, so other methods are not limited to the least square method. However, in order to improve the prediction accuracy, it is common to use a larger number of samplings, that is, the number of actual data. Therefore, conventionally, the wake is predicted using a large number of samplings.
In particular, when drift occurs, if the number of samplings is reduced, the effect is greatly reflected in the prediction of the wake, so that the number of samplings cannot be reduced.

[0005] By the way, in order to prevent the occurrence of an accident or the like, it is indispensable to improve the accuracy of the prediction of the wake. If it is possible to predict the flight position of the scan destination, it will be possible to cope with an accident or the like that may occur more quickly, so it is desired to be able to predict several scan destinations. .

[0006]

However, in the prior art, since the wake is predicted using a fixed sampling number regardless of the flight situation, the wake is predicted by an optimum method according to the flight situation. I couldn't do that.

Further, if the conventional tracking processing technology is used,
It is possible to predict the time one scan ahead, that is, the flight position a short time ahead, but it is not possible to predict the time several scans ahead, that is, the flight position a long time ahead.

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems, and has as its object to provide a track prediction processing apparatus, method, and aircraft monitoring system for accurately predicting a track up to a long time ahead. Is to do.

[0009]

In order to achieve the above object, a wake prediction processing apparatus according to the present invention has a function of detecting a moving position of a moving body by scanning a radar at predetermined time intervals. In a system having
Sampling number setting means for setting a sampling number used for predicting the wake of the moving object based on the detected moving position information of the moving object; and from immediately before the scan for performing the prediction to before the sampling number set by the sampling number setting means. Trajectory prediction processing means for calculating the trajectory of the moving object at the time of scanning for performing prediction using each of the moving position information obtained in each of the scans, wherein the sampling number setting means predicts the trajectory of the moving object The number of samplings to be set is increased as time increases.

Further, the sampling number setting means performs an error and a prediction between a moving position of the moving body at the latest scan when the moving position is actually detected and a predicted moving position of the moving body at the latest scan. A reference sampling number determination processing unit that determines a reference sampling number according to the overall error value obtained based on each movement position information obtained in each scan from immediately before the scanning to a predetermined sampling number before, and a scan that performs prediction. And a sampling displacement number determination processing unit that determines a sampling displacement number according to a total error value obtained based on each moving position information obtained in each scan from immediately before to a predetermined sampling number, and In order to predict the wake at the time of the scan immediately after the latest scan that detected The prediction of the trajectory at the time of scanning performed two or more previously is for setting a value obtained by adding the number of sampling displacement reference sampling number as the sampling number.

Further, the reference sampling number determination processing section increases the reference sampling number as the overall error value obtained from each of the calculated values increases.

Alternatively, the sampling displacement number determination processing section increases the sampling displacement number as the time to be predicted increases.

[0013] Further, the moving object is an aircraft.

[0014] The wake prediction processing method according to the present invention includes:
In a system having a function of detecting a moving position of a moving object by scanning a radar at predetermined time intervals, a sampling for setting a sampling number used for predicting a wake of the moving object based on the detected moving position information of the moving object. Number setting step, and calculating the wake of the moving object at the time of the scan for performing the prediction using each of the movement position information obtained in each scan from immediately before the scan for performing the prediction to before the sampling number set by the sampling number setting means. Track prediction processing step, wherein the number of samplings is increased as the time for predicting the track of the moving object is extended.

In the sampling number setting step, the sampling number is increased as the error between the movement position predicted in the past and the actually detected movement position increases.

Further, the moving object is an aircraft.

An aircraft monitoring system according to the present invention detects a flight position of an aircraft by scanning a radar at predetermined time intervals, and displays the flight position on a screen. A track prediction processing device for predicting a track up to the time and generating track prediction information including the prediction result, and a flight of each aircraft based on the track prediction information generated by the track prediction processing apparatus and information on the entry-prohibited area. While monitoring the situation, having a monitoring processing device that generates alarm information when there is a risk of invading the no-fly zone, and an alarm processing device that issues an alarm based on the alarm information generated by the monitoring processing device, The trajectory prediction processing device is the trajectory prediction processing device described above. It is intended to include at least track prediction information on the number of clicks and sampling displacement ring.

Further, the monitoring and processing device generates intrusion alarm information when the bin set based on the predicted flight position overlaps the intrusion prohibition area, and the bin set based on the predicted flight position is displayed. If the bin overlaps a bin set based on the predicted flight position of another aircraft during the same scan, collision warning information is generated.

[0019]

Preferred embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is an overall configuration diagram showing an embodiment of an aircraft monitoring system according to the present invention. This aircraft monitoring system is a system generally used in air traffic control. FIG. 1 shows a radar sensor 1, a target detection device 2,
A tracking processing device 3, a display device 4, a wake prediction processing device 5, a monitoring processing device 6, and an alarm processing device 7 are shown. Among them, radar sensor 1, target detection device 2, tracking processing device 3
The display device 4 is a device conventionally provided for performing tracking. For aircraft tracking, radar detects the flight position of the aircraft, discriminates the flight of the detected aircraft,
This is done by displaying the flight position. If the radar scans at a predetermined time interval, for example, one revolution every four seconds, the flight position of each aircraft will be updated every four seconds. Then, the radar sets a bin within 4 seconds for performing the next scan and prepares for tracking. The radar sensor 1 and the target detection device 2 are used to detect the flight position of the aircraft when tracking. The tracking processing device 3 includes a tracking processing unit 8, a correlation processing unit 9, and a display processing unit 10. The tracking processing unit 8 obtains the trajectory of each aircraft based on the detected flight positions of the aircraft captured in time series.
The correlation processing unit 9 determines the type (flight name) of the detected aircraft by referring to the database relating to the flight schedule. The display processing unit 10 generates display data for displaying a flight position of each aircraft. The display device 4 displays the flight position of the aircraft on a predetermined display device based on the display data generated by the display processing unit 10.

The aircraft monitoring system according to the present embodiment is characterized in that a wake prediction processing device 5, a monitoring processing device 6, and an alarm processing device 7 are newly provided. In the present embodiment, these devices are provided to monitor the flight status of the aircraft by predicting the wake, not for tracking, and to prevent an accident or the like from occurring.

The track prediction processor 5 is a means for predicting the track up to several scan destinations, and sets the sampling number used for predicting the track based on the detected flight position information of the aircraft. A setting unit 11;
A track prediction processing unit 12 that predicts a track by calculation using, for example, the least squares method using the flight position information of the sampling number set by the sampling number setting unit 11, and the sampling number setting unit 11 and the track prediction processing unit 12 are generated. A track prediction information database 13 for storing track prediction information; The sampling number setting unit 11 includes a reference sampling number determination processing unit 14 and a sampling displacement number determination processing unit 15 that respectively determine a reference sampling number and a sampling displacement number used for setting the sampling number.
And

The monitoring and processing device 6 is provided for each aircraft based on the wake prediction information of each aircraft and the information on the intrusion prohibited area in order to prevent the invasion of the aircraft into the intrusion prohibited area and the collision of the aircrafts. Monitor flight status. Then, when there is a possibility that an accident or the like may occur due to entry into the no-fly zone, alarm information is generated. The intrusion-prohibited area is an area that is actually allowed to fly but must not fly according to regulations. The area where each aircraft is not allowed to fly is a flight area that overlaps with this entry-prohibited area and the bins of other aircraft, and is collectively referred to as a flight-prohibited area in the present embodiment. The alarm processing device 7 issues an alarm according to the alarm information generated by the monitoring processing device 6. The monitoring processing of monitoring the flight status of each aircraft based on the flight position detected by each aircraft and issuing an alarm as necessary has been conventionally performed. However, the monitoring processing device 6 and the alarm processing device according to the present embodiment have been used. 7 performs a characteristic process of generating and outputting warning information based on the flight position information predicted by the wake prediction processing device 5 which is a characteristic component in the present embodiment. Only characteristic processing will be described, and conventional monitoring processing will not be described.

What is characteristic in this embodiment is that the provision of the wake prediction processing device 5 allows not only the flight position at the time of one scan ahead (short time ahead) but also the longer time (long time ahead). The flight position can be predicted. In addition, by setting an appropriate sampling number according to the detected current flight situation or according to the predicted time, the wake is predicted using the flight position information of the sampling number. is there. Specifically, the number of samplings is increased as the prediction time is extended earlier, and the number of samplings is increased as the error increases, so that the wake can be accurately predicted.

In the present embodiment, the wake is predicted using the flight position information of the aircraft scanned in the past represented by the coordinate data. The flight position information is conventionally used in the tracking processing device 3. Data,
I will use that data. Further, since the display processing unit 10 in the tracking processing device 3 also performs the display processing on the display device 4, the display processing function is used. Of course, the wake prediction processing device 5 may directly receive the detection data from the target detection device 2, or the monitoring processing device 6 may have a display processing function.

Further, the present embodiment has a feature in the wake prediction processing, and does not have a feature in the tracking processing. In order to distinguish between the track prediction processing and the tracking processing, the track prediction processing apparatus 5, the monitoring processing apparatus 6, and the alarm processing apparatus 7 are illustrated separately from the tracking processing apparatus 3 in FIG. Figure 1
It is not necessary to provide them separately as in the above.

Here, a method of determining the number of samplings, which is a feature of the present embodiment, will be described.

As described above, the wake is determined by using a method such as the least squares method based on the flight position of the aircraft detected by each scan from the scan immediately before the scan for performing prediction to the past several scans. It can be obtained by smoothing the trajectory. Therefore, the track to be obtained differs depending on the number of data of the detection position of the airplane used for calculation, that is, the number of samplings. For example, if a drift occurs 7 hours before the scan, the wake obtained using the flight position information up to 6 scans is different from the wake obtained using the flight position information incorporating the drift up to 7 scans. Come. And at the time of the next scan that has not been detected yet, if you think in pinpoint, it can be predicted that the aircraft is flying on the line of the wake obtained,
The number of samples of the flight position information used for calculation in predicting the track is a very important factor, and the precision of the track prediction differs depending on this number. In the present embodiment, this sampling number is obtained by combining two types of variables, the reference sampling number and the sampling displacement number. The adjustment of the sampling number will be described with reference to FIG.

FIG. 2 shows an example in which the reference sampling number a is 5 and the sampling displacement numbers b1 and b2 are 2 respectively. Xm-k to Xm indicate the detected flight positions, and Xm is the flight position in the latest scan that actually detected the flight position. On the other hand, Q1, Q2,
Q3 is a flight position in the future, and indicates a predicted flight position of one scan destination, two scan destinations, and three scan destinations, respectively. In the present embodiment, as is apparent from FIG. 2, only the reference sampling number is set as the sampling number for the predicted flight position of one scan destination that is also performed for tracking. The sampling position a = 5, that is, the flight position one scan ahead is predicted using the five flight position information. For the predicted flight position two scan ahead, the sampling number is set by adding the sampling displacement number (b1 = 2) to the reference sampling number (a = 5). In this case, the flight position two scan ahead is predicted using the seven sampling numbers. Further, the predicted flight position three scan ahead is calculated by adding the sampling displacement number (b) to the reference sampling number (a = 5).
1 = 2 and b2 = 2) are added to set the number of samples. In this case, the flight position of three scan destinations is predicted using nine sampling numbers. In the present embodiment, the accuracy of predicting the flight position for a long time is improved by increasing the sampling number used as the time for predicting the flight position for the first scan and the second scan is extended earlier. I have. How to determine the reference sampling number a and the sampling displacement numbers b1 and b2 in this example will be described in detail in the following description of the sampling number setting process.

Next, the wake prediction processing in the present embodiment will be described with reference to the flowcharts shown in FIGS.

In this embodiment, when predicting the flight position n scan destinations, the wake is predicted using the flight position information of the past several scans from immediately before.
As is evident from the above, not only the flight position information actually detected but also the predicted flight position information at the previous time (n-1), (n-2),. I have to. Therefore, even when predicting a long track ahead, one scan ahead, two scan ahead, ...
Then, the flight position of the target n scan destination is predicted while sequentially extending the time from the current aircraft detection position. In this embodiment, a case where n = 3 will be described as an example.

First, the scan destination n is set to 1 (step 1).
10), a reference sampling number determination process is executed (steps 120 and 130). In the present embodiment, the reference sampling number is directly set as the sampling number at the time of the scan immediately after the latest scan in which the flight position is actually detected, that is, the prediction of the flight position at the time of one scan destination. Obtaining the reference sampling number by processing means obtaining the sampling number one scan ahead as it is. Details of the reference sampling number determination processing (step 130) performed by the reference sampling number determination processing unit 14 will be described with reference to the flowchart shown in FIG.

The reference sampling number determination processing unit 14 calculates an error between the flight position detected at the latest scan and the predicted flight position at the time of the scan in the flight position information obtained by actually detecting the flight position. Ed
Is calculated (step 131). Data necessary for the calculation is extracted from the tracking processing device 3 as appropriate. Each flight position is
Since the distance is represented by the coordinate data, an error can be obtained by obtaining the distance of each flight position. In FIG. 6A,
An example is shown in which the detected flight position A1 is slightly shifted from the predicted flight position B1 at the time of the immediately preceding scan. Subsequently, the standard error E of the detection position of the past several scans
s is obtained (step 132). The past several scans are the number of samplings of the detected flight position used for calculating the standard error Es. This may be set to a value unique to the system, or may be performed in steps 134 to 1 performed in the past.
38 results may be used. In the present embodiment, the latter method is adopted.

For example, if the sampling number is set to 3, the flight positions detected in the scans up to three scans before the flight position detected in the immediately preceding scan, that is, the flight position information of the flight positions A1, A2, and A3 Is used to determine the standard deviation, and the standard deviation is calculated by dividing the standard deviation by the square root of the sampling number. This value is corrected so as to be regarded as a relative error between the other flight positions A2 and A3 with respect to the flight position A1 at the time of the immediately preceding scan, and further corrected by taking into account components such as the flight speed. Find Es. Steps 131 and 132 need not be performed in this order, but may be reversed or may be performed simultaneously.

Next, the reference sampling number determination processing section 14
Calculates the overall error E by multiplying the error Ed and the standard error Es obtained in the above-described processes by the error parameters a and b, respectively, and adding them (step 133). The balance of the errors Ed and Es is adjusted by the error parameters a and b. Then, the reference sampling number is obtained by comparing the calculated overall error E with a preset threshold value.

Since the general error E is a value obtained from past performance data, a large value means that the aircraft deviates more than predicted from the predicted track, so that the aircraft is turning, It is determined that drift has occurred. Therefore, it is necessary to more effectively perform the smoothing in order to ensure the accuracy of the prediction. For this reason, it is desired to predict the wake by using the flight position information of a larger sampling number. On the other hand, when the overall error E is small, it is determined that the vehicle has not turned and that no drift has occurred. Therefore, in this case, it can be said that the accuracy does not decrease even if the wake is predicted with the flight position information of a relatively small number of samplings. In this embodiment, three levels of reference sampling numbers can be set according to the value of the general error E in order to set different sampling numbers. That is, if the overall error E is equal to or less than the threshold of level 1, the reference sampling number of level 1 is set (steps 134 and 135). If the overall error E is larger than the threshold of level 1 and equal to or smaller than the threshold of level 2, the reference sampling number of level 2 is set (steps 136 and 137). The number is set (steps 136, 138). In the present embodiment, the reference sampling number is set to be larger as the value of the general error E is larger. Therefore, when the reference sampling numbers of each level are a1, a2, and a3, respectively, the relationship of a1 ≦ a2 ≦ a3 is obtained. Become. For example, when it is determined that drift has occurred due to the large overall error E, the level 3 reference sampling number is set. When the aircraft is turning, it is determined that the reference sampling number of level 2 is set when it is determined that the aircraft is turning because the overall error E is large, though not as high as level 3.
Furthermore, when it is determined that the aircraft is traveling straight because the overall error E is small, the level 1 reference sampling number is set. The threshold value is set while appropriately changing it in consideration of factors such as the measurement accuracy of the radar used.

Returning to FIG. 3, the sampling number setting unit 11
Sets the number of samplings (step 150). Here, since the flight position of one scan destination is predicted, the reference sampling number determined as described above is used as it is as the sampling number. The wake prediction processing unit 12 obtains a wake using the least squares method based on the flight position information of the sampling number obtained as described above, and predicts the flight position one scan ahead with reference to the flight speed of the aircraft ( Step 160). The predicted flight position information represented by the coordinate data, the overall error obtained in the preceding process, the level of the overall error, the reference sampling number, and the like are used as the track prediction information for one scan destination as the track prediction information database 13.
(Step 170).

In this embodiment, since the flight position is predicted up to three scan destinations, the process proceeds to the process of predicting the time flight position at two scan destinations (steps 180 and 190). In order to obtain the number of samplings at the time of the second and subsequent scans, it is necessary to perform processing (step 140) for determining the number of sampling displacements in advance.
The details of the sampling displacement number determination processing (step 140) performed by the sampling displacement number determination processing section 15 will be described with reference to the flowchart shown in FIG.

The sampling displacement number determination processing section 15 obtains the standard error Es of the predicted / detected positions of the past several scans (step 141). The method of calculating the standard error Es may be the same method as the reference sampling number determination processing. However, when the prediction target is the second or subsequent scan, there is no detected flight position data at the time of the immediately preceding scan, so that the predicted flight position obtained in step 160 is regarded as the detected flight position and the standard error Es is obtained. For example, if the sampling number is 3
In the case of, as shown in FIG.
The flight positions A1 and A2 detected as 1 will be used.
Although the past several scans may be understood in the same manner as the reference sampling number determination processing, in the present embodiment, the reference sampling number obtained in the prediction processing one scan ahead is used. Subsequently, a measurement error Er is obtained (step 142). This expresses the measurement accuracy of the radar as an error.

Next, the sampling displacement number determination processing unit 15
Calculates the overall error E by multiplying the standard error Es and the measurement error Er obtained in each of the above processes by the error parameters b and c, respectively, and then adding them (step 143). The balance of the errors Es and Er is adjusted by the error parameters b and c. Then, the reference sampling number is obtained by comparing the calculated overall error E with a preset threshold value. The concept of the overall error in the sampling displacement number determination process is the same as the reference sampling number determination process described with reference to FIG.

In the processing flow (steps 144 to 148) for determining the number of sampling displacements at each level by comparing the value of the next general error E with each threshold value, the reference sampling number is determined in the reference sampling number determination processing. Since the processing flow at this time is basically the same (steps 134 to 138), detailed description is omitted. The sampling displacement number determined in steps 144 to 148 is set so that the larger the value of the total error E is, the larger the sampling displacement number is, as in the case of the reference sampling number.
Assuming that b21 and b31, the relationship is b11 ≦ b21 ≦ b31. The sampling displacement number determined here corresponds to b1 described in FIG.

Returning to FIG. 3, the sampling number setting unit 11
Sets the number of samplings (step 150). Here, since the flight position of two scan destinations is predicted, the reference sampling number determined in the prediction processing of one scan destination is read from the wake prediction information database 13, and the sampling displacement number determined in the sampling displacement number determination processing is added to the reference sampling number. Is added to the sampling number. The wake prediction processing unit 12 obtains a wake by using the least squares method based on the detected flight position data of the sampling number obtained as described above, and calculates the flight position two scan ahead by referring to the flight speed of the aircraft. (Step 160). Then, the predicted flight position information represented by the coordinate data, the overall error obtained in the preceding process, the level of the overall error, the reference sampling number, and the like are used as the track prediction information for two scan destinations as the track prediction information database 1.
3 (step 170).

Next, a flight position is predicted three scan destinations. This process is the same as the above-described two scan destination prediction process, and a description thereof will be omitted. However, in the processing flow for determining the number of sampling displacements (steps 144 to 148), the number of sampling displacements at three scan destinations does not necessarily have to be the same as the number of sampling displacements at two scan destinations. That is, if the sampling displacement number for two scan destinations at level 1 is b11 and the sampling displacement number for three scan destinations at level 1 is b12, b11 and b12 can be set to different values. Of course, if the number of sampling displacements at each level is b12, b22, and b32 even during three scans, the relationship of b12 ≦ b22 ≦ b32 is maintained. The sampling displacement number determined here corresponds to b2 described in FIG.

Returning to FIG. 3, the sampling number setting unit 11
Sets the number of samplings (step 150),
When predicting the flight position of three scan destinations, the reference sampling number determined in the one scan destination prediction process and the sampling displacement number determined in the two scan destination prediction process are read from the wake prediction information database 13,
The value obtained by adding the sampling displacement number determined in the sampling displacement number determination processing to this is set as the sampling number. The wake prediction processing unit 12 obtains a wake using the least squares method based on the detected flight position data of the sampling number obtained as described above, and calculates a flight position three scan destinations with reference to the flight speed of the aircraft. (Step 160). Then, the predicted flight position information represented by the coordinate data, the overall error obtained in the preceding process, the level of the overall error, the reference sampling number, and the like are stored in the wake prediction information database 13 as wake prediction information for three scan destinations. (Step 170). As described above, the flight position of each aircraft at the time of each future scan can be predicted.

When the trajectory prediction processing unit 5 predicts the flight position of each aircraft, the monitoring processing unit 6 calculates the aircraft's predicted flight position and intrusion prohibited area included in the wake prediction information at each scan. Then, processing for generating alarm information is performed as necessary to avoid collision. This monitoring process will be described with reference to the flowchart shown in FIG.

The monitoring processor 6 generates bins based on the flight positions (pinpoints) obtained in the above processing (step 201). Regarding the setting of the bin, the same conventional method is used. In addition, although the predicted flight position at each scan is obtained by pinpoint, it actually exists somewhere within the set range of the bin in consideration of an error or the like. Therefore, the “predicted position” in the monitoring processing described here is exactly the bin setting range.

In the subsequent processing, alarm information is generated. First, it is determined whether or not the predicted position at the time of each scan predicted on each aircraft overlaps the intrusion prohibition area (step 202). Since each piece of information to be compared can be represented as coordinate data, it can be easily determined whether or not they overlap. The same applies to the subsequent determination processing of whether or not they overlap. Here, when it is determined that they overlap, it is possible to determine that the corresponding aircraft may enter the intrusion prohibited area at the time of the corresponding scan, and the monitoring processing device 6 issues an intrusion alarm indicating that fact. Then, intrusion alarm information is generated (step 203). In the intrusion alarm information, information about which aircraft (flight) may enter at which position in the intrusion prohibition area and when is set. Also, when there is no possibility that all the predicted positions enter the intrusion prohibited area,
If an intrusion alarm has been set, it is canceled (steps 204 and 205). In this way, the process of monitoring intrusion into the intrusion prohibited area is performed.

Subsequently, the monitoring processor 6 determines whether or not the predicted positions in each scan predicted in each aircraft overlap each other in the same scan (step 206). When the predicted positions of the aircraft at the same scan overlap each other, it can be determined that there is a risk of collision at the time of the scan. Therefore, the monitoring processing device 6 sets a collision warning indicating that fact, and sets the collision warning information. Is generated (step 207). In the collision warning information, information about which aircraft (flight) is likely to collide when and where is set. If there is no possibility of collision, if a collision warning is set, it is canceled (steps 208 and 209). Thus, the collision monitoring process is performed.

In the present embodiment, in order to explain the characteristic prediction of the wake of a long time (n scans) ahead, the wake prediction processor 5 generates the wake prediction information of the n scan destination and then performs the monitoring process. Although the description has been made such that the device 6 performs the monitoring processing, the monitoring processing device 6 performs the monitoring process every time the wake prediction processing device 5 generates the wake prediction information for one scan in order to pursue real-time performance. You may.

As shown in the flowchart of FIG. 8, the alarm processing performed by the alarm processing device 7 outputs an intrusion alarm if an intrusion alarm has been set by the monitoring processing device 6 (steps 301 and 302). When the intrusion alarm has been released, the output of the intrusion alarm is stopped (step 30).
3, 304). If a collision warning is set by the monitoring processor 6, a collision warning is output (step 30).
5,306), when the set collision warning is released, the output of the collision warning is stopped (steps 307, 30).
8).

According to the present embodiment, the flight position ahead of a long time can be predicted as described above. In addition, when predicting a long track ahead, it is considered that the prediction accuracy of the track decreases as the prediction time increases, but in the present embodiment, the number of samplings increases as the time ahead predicts. Since the number is increased, a decrease in prediction accuracy can be suppressed as much as possible. In other words, the prediction accuracy for the short-term prediction does not decrease relatively as compared with the long-time prediction, so the prediction is performed with a smaller sampling number. By reducing the number of samplings, the prediction processing time can be reduced, and the prediction result can be immediately used for accident prevention and the like.

Further, in the present embodiment, even when predicting the flight position during a certain scan, an error based on the actual performance is evaluated, and the number of samples is increased or decreased according to the magnitude of the error. The accuracy of wake prediction can be further improved. For example, empirically, the sampling number is set to 5 when the overall error is small and to 5 when the total error is large.
If the value is set to 7 in the case of, the error between the actually detected position and the predicted position is reduced. If the sampling number is larger than 7, the smoothing is too large, and it becomes difficult to detect the drift.
With a smaller sampling number, the effect of the drift is amplified and appears at the predicted flight position. In addition, as for the number of sampling displacements at the time of prediction of three scan destinations, a degree of adding 1 or 2 to the reference sampling number is suitable for performing smoothing. Therefore, the reference sampling number and the sampling displacement number are adjusted so that the sampling number falls within the above range. Of course, depending on the detection position, there is a case where a sampling number of 8 or more or less than 5 is effective.
It does not mean that it must be 5 or more and 7 or less. If the number of sampling displacements is set to 0, prediction will be performed with the same fixed sampling number as in the past, but in this case, the number of detected flight position data used to obtain the predicted flight position at the time of the scan after 2 , The prediction accuracy is more likely to decrease. If the number of sampling displacements is always 1, the same number of detected flight position data can be always used even when the flight position of n scan destinations is predicted, so that a decrease in prediction accuracy can be prevented. If the number of sampling displacements is always two, predicting an earlier time will use more detected flight position data, and a smoother predicted flight position can be obtained.

By the way, if it is possible to predict for a long time, the following effects are obtained. Usually, as a flow of a process for avoiding a collision, a flight position is predicted, bin overlap is checked, and if there is a possibility of a collision, a corresponding aircraft is notified. The pilot of the aircraft changes the route according to the notification to avoid collision. For example, if this series of processing takes 12 seconds, and if the interval (one scan) at which prediction is performed is 4 seconds, this collision cannot be avoided even if only one scan destination is predicted with high accuracy. That is, it is necessary to predict the wake of three scan destinations. In this case, this embodiment, which can predict a long time ahead, is effective. Furthermore, in the present embodiment, prediction accuracy can be improved by increasing the number of samplings instead of simply performing prediction for a long time.

The present embodiment is characterized in that a wake is predicted, and no reference is made to tracking. However, if attention is paid to the prediction processing of one scan destination in the present embodiment, the characteristic wake prediction processing in the present embodiment can be applied to the tracking processing, thereby reducing the bin size in the tracking processing. And the like.

Further, in the present embodiment, an aircraft monitoring system assuming an aircraft as a moving body has been described as an example. However, the wake prediction processing device 5 according to the present embodiment is not limited to other moving bodies such as birds and ships. For example, the present invention can be applied to a system for predicting a moving position.

[0056]

According to the present invention, the flight position ahead of a long time can be predicted, and when predicting the wake of a long time ahead, the sampling number is increased as the time to be predicted is extended earlier. As a result, a decrease in prediction accuracy can be minimized. In other words, since the prediction for the short time is made with a smaller number of samplings compared to the long time, the prediction for the short time can be processed in a short time.

Further, the error is evaluated based on the past results, and the number of samplings is increased or decreased according to the magnitude of the error, so that the accuracy of the prediction of the wake can be further improved. That is, if the error is large, the number of samplings used to obtain the wake prediction is increased, so that a decrease in the prediction accuracy can be suppressed as much as possible. As described above, according to the present invention, it is possible to set the optimum number of samplings when calculating the prediction of the wake according to the moving state of the moving body, so that the wake can be more efficiently and accurately calculated. You can make predictions.

Further, according to the present invention, an alarm can be issued when there is a possibility that the moving object may enter the prohibited area as a result of predicting the moving position of the moving object. Can be predicted with high accuracy, so that the number of times a false alarm is issued can be minimized.

[Brief description of the drawings]

FIG. 1 is an overall configuration diagram showing an embodiment of an aircraft monitoring system according to the present invention.

FIG. 2 is a diagram for explaining a method of adjusting the number of samplings in the present embodiment.

FIG. 3 is a flowchart showing a wake prediction process according to the embodiment.

FIG. 4 is a flowchart showing a reference sampling number determination process in the present embodiment.

FIG. 5 is a flowchart showing a sampling displacement number determination process in the present embodiment.

FIG. 6 is a conceptual diagram showing a positional relationship between a predicted flight position and a detected flight position in the present embodiment.

FIG. 7 is a flowchart illustrating a monitoring process according to the present embodiment.

FIG. 8 is a flowchart illustrating an alarm process according to the present embodiment.

[Explanation of symbols]

Reference Signs List 1 radar sensor, 2 target detection device, 3 tracking processing device, 4 display device, 5 track prediction processing device, 6 monitoring processing device, 7 alarm processing device, 8 tracking processing unit, 9 correlation processing unit, 10 display processing unit, 11 Sampling number setting unit, 12 track prediction processing unit, 13 track prediction information database, 14 reference sampling number determination processing unit, 15
Sampling displacement number determination processing unit.

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 5H180 AA26 CC14 DD01 LL01 LL02 LL04 LL06 5J070 AC01 AE04 AH04 AH14 AH19 AK22 BB04 BB06 BB20 BF12

Claims (10)

[Claims] 1. A system having a function of detecting a moving position of a moving object by scanning a radar at predetermined time intervals, wherein sampling used for predicting a wake of the moving object based on the detected moving position information of the moving object. Sampling number setting means for setting the number, and movement at the time of scanning for performing prediction using each movement position information obtained in each scan from immediately before the scan for performing prediction to before the sampling number set by the sampling number setting means. Wake prediction processing means for calculating the wake of the body, and wherein the sampling number setting means increases the number of samplings set as the time for estimating the trajectory of the moving body increases. Track prediction processing device. 2. The sampling number setting means performs an error and a prediction between a moving position of the moving object at the latest scan when the moving position is actually detected and a predicted moving position of the moving object at the latest scan. A reference sampling number determination processing unit that determines a reference sampling number according to an overall error value obtained based on each movement position information obtained in each scan from immediately before the scanning to a predetermined sampling number before, and a scan for performing prediction And a sampling displacement number determination processing unit that determines a sampling displacement number according to the total error value obtained based on each moving position information obtained in each scan from immediately before to a predetermined sampling number, and Set the reference sampling number as the sampling number to predict the wake at the time of the scan immediately after the latest scan that detected the position, 2. The track prediction processing apparatus according to claim 1, wherein a value obtained by adding a sampling displacement number to a reference sampling number is set as a sampling number in predicting a track at the time of scanning performed two or more times earlier. 3. The reference sampling number determination processing unit,
3. The wake prediction processing device according to claim 2, wherein the reference sampling number is increased as the overall error value obtained from each of the calculated values increases. 4. The sampling displacement number determination processing unit,
3. The wake prediction processing apparatus according to claim 2, wherein the number of sampling displacements is increased as the time to be predicted is extended earlier. 5. The wake prediction processing device according to claim 1, wherein the moving object is an aircraft. 6. A system having a function of detecting a moving position of a moving object by scanning a radar at predetermined time intervals, wherein sampling used for predicting a wake of the moving object based on the detected moving position information of the moving object. A sampling number setting step of setting the number, and a movement at the time of the scan for performing the prediction using each movement position information obtained from each scan from immediately before the time of the scan for performing the prediction to the time before the number of times of sampling set by the sampling number setting means A track prediction processing step of calculating a track of the body, the method comprising: increasing the number of samplings as the time for predicting the track of the mobile body increases. 7. The wake prediction according to claim 6, wherein in the sampling number setting step, the sampling number is increased as an error between a movement position predicted in the past and a movement position actually detected increases. Processing method. 8. The wake prediction method according to claim 6, wherein the moving object is an aircraft. 9. An aircraft monitoring system which detects a flight position of an aircraft by scanning a radar at predetermined time intervals and displays the flight position on a screen, predicts a wake up to several scan destination times. A track prediction processing device that generates track prediction information including the prediction result thereof, and monitors the flight status of each aircraft based on the track prediction information generated by the track prediction processing device and information on the entry-prohibited area, and A monitoring processing device that generates alarm information when there is a possibility of intruding into, and an alarm processing device that issues an alarm based on the alarm information generated by the monitoring processing device. 5. The wake prediction processing apparatus according to 5, wherein each of the calculated error values, reference sampling numbers, and sampling Aircraft monitoring system, characterized in that included in at least track prediction information number. 10. The monitoring and processing device, if a bin set based on the predicted flight position overlaps the intrusion prohibition area, generates intrusion alarm information, and the bin set based on the predicted flight position is 10. The aircraft surveillance system according to claim 9, wherein collision warning information is generated when the bin overlaps a bin set based on a predicted flight position of another aircraft during the same scan.