JPH0769299A - Pilot landing assisting device - Google Patents

Abstract

PURPOSE:To previously predict the course of flight at forced landing so as to make the forced landing safe by making the course of flight from the position of an own craft to a point capable of being landed by a flight course making means, when the own craft, is troubled. CONSTITUTION:This pilot landing assisting device is provided with a navigation sensor 6 detecting the position of an own craft, an engine monitor 5, a map generation 3 storing map data, and a meteorological sensor 11, and the course of flight is computed by a flight course computing part 2 based on respective output signals. Respective data are computation-processed by a display processing part 4, and the computation-processed data are displayed on the screen of a CRT instrument 9. A touch panel sensor 10 is provided on the screen of the CRT instrument 9, and a signal indicated by this is input to an input processing part 8. Fuzzy inference is performed in a course selection processing part 7 based on the course data output from the flight course computing part 2 so as to evaluate the course of flight and selectively process, and the inference result is displayed on the screen.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION The present invention uses fuzzy reasoning to select the best of several candidates,
The present invention relates to a pilot landing support device for assisting a pilot by calculating a condition necessary for achieving the purpose, and particularly by calculating and displaying a safer flight route when an aircraft such as a helicopter makes an emergency landing.

[0002]

2. Description of the Related Art Conventionally, when a pilot operates an airplane, his / her position is confirmed by looking at the instruments that detect and display the three-dimensional position and attitude of the aircraft. Also, INS
(Inertial navigation system) and GPS (Grobal Positioning Syste)
By using m) etc., it is possible to perform guided flight along a predetermined flight route from the starting point to the destination.

[0003]

However, when an engine failure of the aircraft, a trouble of the fuel system or the like occurs, and the aircraft is forced to make an emergency landing, the pilot looks for a landable point on the ground by himself and It is necessary to determine the flight route to safely land on the point. At this time,
It requires a lot of skill for the pilot to accurately judge the landing possibility in a short time, and there is a problem that safe landing becomes extremely difficult especially in bad weather conditions.

In order to solve the above-mentioned problems, an object of the present invention is to provide a pilot landing support capable of promptly teaching a suitable flight course to a pilot when a trouble such as an engine failure of an aircraft occurs and it makes a landing accidentally. It is to provide a device.

[0005]

DISCLOSURE OF THE INVENTION The present invention provides a self-position detecting means for detecting a self-position, a self-state detecting means for detecting a self-state, and a map information storing means. Based on the map information storage means, the signal from the own machine position detection means, the signal from the own machine state detection means and the signal from the map information storage means, the own machine position, the own machine state, and the surroundings of the own machine In a pilot landing support device comprising a display means for displaying a map on the screen, in the case of failure of the aircraft, flight course creation means for creating a flight course from the aircraft position to the landing point, A pilot landing support apparatus comprising: a flight course evaluation means for determining the best flight course using fuzzy inference when there are a plurality of flight courses.

The present invention further comprises a course length calculating means for calculating a course length from the position of the aircraft to a landing point.
Meteorological condition detecting means for detecting meteorological conditions around the own aircraft, and for evaluating the altitude of the own aircraft by using fuzzy inference based on the signal from the course length calculating means and the signal from the meteorological condition detecting means And own altitude evaluation means.

[0007]

According to the present invention, based on the own machine position signal sent from the own machine position detecting means, the own machine state signal sent from the own machine state detecting means, and the map information signal sent from the map information storing means, The pilot can easily confirm the flight position of the aircraft by displaying the aircraft position, the aircraft state, and a map around the aircraft on the screen. Further, when the own aircraft is out of order, the flight course creating means creates a flight course from the own aircraft position to the landing possible point, so that the flight course at the time of emergency landing can be predicted in advance. In addition, the flight course evaluation means uses fuzzy reasoning to determine the best flight course from among the plurality of flight courses, so that the pilot can follow the best course for safe landing.

Further, the course length calculating means calculates the course length from the position of the own aircraft to the landing possible point, and based on the weather conditions around the own aircraft sent from the weather condition detecting means, the own altitude evaluation means, By evaluating the altitude of the aircraft using fuzzy reasoning, it is possible to safely and accurately predict the flight possibility to the landing point during an emergency landing.

[0009]

1 is a block diagram showing the configuration of a pilot landing support system according to an embodiment of the present invention. The pilot landing support device 1 includes a navigation sensor 6 for detecting the position of the aircraft, an engine monitor 5 for detecting the state of the aircraft, particularly an engine state, a map generator 3 for storing map data, Meteorological sensor 11 for detecting the weather conditions around the aircraft, particularly wind direction and wind speed, own position signal sent from navigation sensor 6, engine status signal sent from engine monitor 5, map data sent from map generator 3, and A flight course calculation unit 2 for calculating a flight course based on the wind direction and wind speed signal sent from the weather sensor 11, and data such as a position of the aircraft, a state of the aircraft, a map around the aircraft, a flight course and weather conditions. A display processing unit 4 for processing, a CRT (cathode ray tube) instrument 9 for displaying the arithmetically processed data on a screen, and a C
A touch panel sensor 10 for indicating the position of the RT instrument 9 on the screen, and an input processing unit 8 for processing a touch panel input signal sent from the touch panel sensor 10.
Based on the pilot input signal sent from the input processing unit 8 and the course data output from the flight course calculation unit 2, the flight course is evaluated and selection processing is performed using fuzzy inference, and the inference result is displayed. It comprises a course selection processing unit 7 for outputting to the unit 4.

The navigation sensor 6 is equipped with the above-mentioned INS and GPS and can measure the three-dimensional position and three-dimensional attitude of the own vehicle with reference to a predetermined ground point.

The engine monitor 5 measures engine conditions such as engine speed, temperature, and vibration, and judges that the engine is abnormal when these values exceed a predetermined reference value.

The meteorological sensor 11 measures the wind direction, the wind speed, the temperature, and the like with respect to its own device.

The map generator 3 is for generating a topographical map on the ground and an altitude distribution of mountain ranges at an arbitrary magnification by designating a region using the latitude and longitude of the earth.

The touch panel sensor 10 is a CRT instrument 9
The touch panel sensor 10 is formed of a translucent member so as not to interfere with the screen display, and the pilot 90 contacts the touch panel sensor 10 with a finger or the like to output the contact position on the screen.

The pilot landing support apparatus 1 having such a configuration is installed around the pilot's seat of the pilot 90.

FIG. 2 is a flow chart showing an example of the operation of the pilot landing support system shown in FIG. When the engine monitor 5 detects an engine failure, the procedure starts from step a1 and, in step a2, an engine failure warning is displayed on the screen of the CRT instrument 9.

FIG. 3 shows an example of an engine failure warning display. When the aircraft is a helicopter, when an engine failure is detected, the pilot 90 is notified of the engine failure by displaying a screen as shown in FIG. 3 until stable autorotation flight is started. An engine failure emergency symbol 21 is displayed in both upper corners and lower center of the screen, and continues to blink until stable autorotation flight is started. Also, as in normal flight, a vertical movement rate meter 22 showing the vertical movement rate (foot altitude change per minute: fpm) of the aircraft is displayed on the left side of the screen, and the azimuth angle of the aircraft (from the north azimuth to the clockwise direction) is displayed. The azimuth meter 23 showing the angle of deg) is displayed at the top of the screen and the altitude (ft) of the aircraft is displayed.
Is displayed on the right side of the screen. Further, a meter indicating speed meter 25 indicating the flight speed (kt) of the own aircraft is displayed on the lower right side of the screen, and when the range of 40 to 80 kt is exceeded, it blinks. Further, a rotor rotation speed meter 26 showing the rotation speed (%) of the rotor of its own machine is displayed on the lower left side of the screen, and blinks when it exceeds the range of 85 to 105%. It should be noted that in the center of the screen, the own-machine symbol 20 and the contour lines of the mountain 40 are displayed.

Returning to FIG. 2, the process proceeds to the next step a3, and based on the own position signal from the navigation sensor 6 and the map data from the map generator 3, a topographic map and a flat ground without obstacles are displayed. CRT instrument 9 at the landing point
Displayed on the screen of. The landable points are stored in the map generator 3 in advance.

FIG. 4 is an example of a screen display of landing possible points. When the helicopter enters steady autorotation flight, the reachable range is calculated and displayed based on the ascent / descent rate and speed at that time. At the same time, the candidate landing points existing within the reachable range are judged by the fuzzy reasoning to determine whether they are good or bad, and are ranked, and displayed together with the numbers indicating the ranking. The pilot 90 selects a desired place from the displayed landing display points and inputs it by the touch panel sensor 10. The engine failure emergency symbol 21 displayed in both upper corners of the screen is changed to a landing point selection symbol 27 to prompt the pilot 90 to select a landing point. Further, a mark 30 indicating the reachable range of the aircraft is displayed in the center of the screen, and within that range, the landing candidate symbols 28 and 29 indicating the landing candidate points are determined by the judgment order (“1” and “2 in the screen”). , Etc.) is displayed. The order of landing candidate points is determined by setting all possible courses for each candidate point, determining those courses by fuzzy reasoning, and determining which course has a better course.

Returning to FIG. 2, proceeding to the next step a4, the pilot 90 selects from the landing candidate points displayed on the screen of the CRT instrument 9 the touching point sensor 10 as to the point at which the aircraft is about to land. To select one. In the next step a5, some courses from the current position of the aircraft to the selected landing point are created.

FIG. 5A is a flow chart showing an example of a method of creating a course from the position of the aircraft to the landing point. First, starting from step b1, in step b2, the topographic map displayed on the screen of the CRT instrument 9 is displayed in FIG.
Set a virtual lattice as shown in FIG.
At 3, the node point to be the start point is determined based on the current position of the aircraft and the flight direction. Next, adjoining node points existing in directions within ± 90 ° to the left and right based on the approach direction to the node point (points a to e in FIG. 5B)
Then, in step b5, it is determined whether or not the distance from the selected node point to the target is smaller than the current distance from the own position to the target. If the latter is smaller, the selected node point is selected. Is approaching the target, and the process proceeds to the next step b6, but if the selected node point is away from the target, the process returns to step b4 to evaluate another node point. In the next step b6,
Judge whether the expected altitude above the selected node point is higher than the terrain elevation at the selected node point,
If the predicted altitude is lower than the altitude, the aircraft will contact the ground surface, and the process returns to step b4 to evaluate another node point.

In the next step b7, step b
The selected node point satisfying the conditions of 5 and b6 is determined as the waypoint of the course, and in step b8, it is judged whether or not the distance from the selected node point to the target is almost 0, that is, the grid interval or less, and the target is determined. Steps b4 to b8 are repeated until it approaches the neighborhood. Thus, in the next step b9, 1 from the current position of the aircraft to the target is obtained.
The book course is completed. Further, if it is necessary to create another course in the next step b10, steps b4 to b9 are repeated to set some courses having selected node points satisfying the conditions of steps b5 and b6, and The process ends at step b11. Note that FIG. 5 (c)
Shows an example in which each course from the current position of the aircraft to the target two landing candidate points A and B is set.

Returning to FIG. 2, the process proceeds to the next step a6, and the flight course length is too long from the course created as described above by using the usual numerical calculation, and the flight point is clearly the landing point. Filter out possible courses by deleting courses that cannot be reached. At step a7, the quality of the remaining flight course is evaluated using fuzzy reasoning.

FIGS. 6A to 6E are membership functions used when the pilot landing support apparatus 1 according to the present invention executes fuzzy inference. There are 25 fuzzy control rules, for example, as shown in the following example.
It is further classified into five categories.

A. Rule regarding average ground altitude of flight course (Fig. 6 (a)) (1) if Average of ground altitude is very low (TL) then Course quality is bad (2) if Average of ground altitude is low (LOW) then Good or bad of course is a little bad (3) if Average of ground altitude is medium (MED) then Good or bad of course is medium (4) if Average of ground altitude is high (HIGH) then Good or bad of course is a little good (5) if Average of ground altitude is very high (TH) then good or bad of course is good b. Rule regarding flight course length (Fig. 6 (b)) (6) if Flight course length is Very short (TN) then Course quality is Medium (7) if Flight course length is Low (NEAR) then course Good or bad is good (8) if Flight course length is medium (MED) then Good or bad of course is a little good (9) if Flight course length is long (HIGH) then Good or bad of course is medium (10) if Flight course length is Very long (TH) then Course is good or bad c. Rules for altitude clearance above the target landing point (Fig. 6
(C)) (11) if Altitude margin is very low (TL) then course quality is bad (12) if Altitude margin is low (LOW) then course quality is a little bad (13) if Altitude margin is medium (MED) then Course quality is a little good (14) if Altitude margin is high (HIGH) then Course quality is good (15) if Altitude margin is very high (TH) then Course quality is medium d. Rule regarding total turning angle on flight course (Fig. 6 (d)) (16) if Total turning angle is very small (VS) then Good or bad of course is good (17) if Total turning angle is small ( SMALL) then good or bad of course is a little good (18) if total turning angle is medium (MED) then good or bad of course is medium (19) if total of turning angle is large (LARGE) then good or bad of course is a little bad (20) if Total turning angle is very large (VL) then Course quality is bad e. Rule regarding angle between wind direction and approach direction at target landing point (Fig. 6 (e)) (21) if Angle between wind direction and approach direction is very small (V
S) (Tail wind) then good or bad of course is very bad (22) if angle between wind direction and approach direction is small (SMALL) then good or bad of course is bad (23) if angle between wind direction and approach direction is medium ( (MED)
[Crosswind] then good or bad of course is a little bad (24) if angle between wind direction and approach direction is large (LARGE) then good or bad of course is a little good (25) if angle between wind direction and approach is is very large (V
L) [head wind] then good or bad of the course is very good Regarding the good or bad of the course, seven fuzzy sets "Very bad (VB), bad (BAD), a little bad (LB), medium (ZO), a little good" (LG), good (GOOD), very good (VG) ”.

Next, a specific example of calculating the membership function of each flight course selected as a candidate in step a6 will be described. First, when the average value of the ground altitude is, for example, Xa when evaluating a certain flight course (see FIG. 6A), the conformity of rule (2) is about 0.7, and rule (3) ) Is about 0.3, the fuzzy sets that show the quality of the course are shown in Fig. 6 as "a little bad (LB)".
The function shown in (f) and "medium (ZO)" become the function shown in FIG. 6 (g).

Next, when the flight course length is, for example, Xb (see FIG. 6 (b)), the conformity of rule (8) is about 0.7 and the conformity of rule (9) is about 0. .3, the fuzzy sets indicating the quality of the course are, respectively, “a little good (LG)” is the function shown in FIG. 6 (h) and “intermediate (ZO)” is a function shown in FIG. 6 (i). Become.

Similarly, when the altitude margin is, for example, Xc (see FIG. 6C), the conformity of rule (13) is about 0.4 and the conformity of rule (14) is about 0. .6
Therefore, in the fuzzy sets indicating the quality of the course, “slightly good (LG)” is the function shown in FIG. 6 (j) and “good (GOOD)” is the function shown in FIG. 6 (k).

Next, when the total of the turning angles is, for example, Xd (see FIG. 6D), the conformity of rule (18) is about 0.6 and the conformity of rule (19) is about. 0.4
Therefore, in the fuzzy sets indicating the quality of the course, "medium (ZO)" is the function shown in FIG. 6 (l) and "a little bad (LB)" is the function shown in FIG. 6 (m).

Next, when the angle between the wind direction and the approach direction is Xe (see FIG. 6 (e)), rule (2)
Since the goodness of fit of 4) is approximately 0.6 and the goodness of fit of rule (25) is approximately 0.4, the fuzzy sets indicating the quality of the course are shown in FIG. The function shown in n) and "Very good (VG)" becomes the function shown in FIG.

The membership function shown in FIG. 6 (p) can be created by adding all the fuzzy sets indicating the quality of the course thus obtained. The membership functions for other courses are shown in FIG.
It is created as shown in (q) and (r).

Returning to FIG. 2, the process proceeds to the next step a8 to perform defuzzification by calculating, for example, the barycentric coordinates of the membership function of each course, and the grade distribution function is converted into one numerical value. Figure 6
The membership functions shown in (p), (q), and (r) take numerical values Y1, Y2, and Y3 as barycentric coordinates, respectively.

In step a9, the obtained numerical value Y
Numerical value Y1 located on the most "good" side of 1, Y2, Y3
The flight course that takes is determined as the best flight course, and in step a10, the best course and the next runner course determined in this way are displayed on the screen of the CRT instrument 9,
The process ends at step a10.

FIG. 7 is an example of a screen display of the recommended flight course. On the screen, the top 3 courses with good conditions among the courses from the aircraft symbol 20 to the landing point symbol 35
1, 32, 33 are displayed together with the ranking (“1”, “2”, etc. in the screen). On the upper left side of the screen, a landing point direction symbol 36 showing the direction of the selected landing point and the distance from the current position is displayed, and the pilot 90 performs an autorotation flight according to the first course of the courses on the screen. As a result, safe and accurate landing can be implemented.

FIG. 8 (a) is a flowchart showing another operation example of the pilot landing support system shown in FIG.
Here, an example of evaluating the altitude of the aircraft using fuzzy inference will be described. When the engine monitor 5 detects an engine failure, the procedure starts from step c1, and in step c2, an engine failure warning is displayed on the screen of the CRT instrument 9 as shown in FIG. In the next step c3, as shown in FIG. 4, based on the own-vehicle position signal from the navigation sensor 6 and the map data from the map generator 3, a landing possible point such as a topographic map and a flat land without obstacles is determined. It is displayed on the screen of the CRT meter 9. In the next step c4, the pilot 90 selects one of the landing candidate points displayed on the screen of the CRT instrument 9 with the touch panel sensor 10 from which one is about to land.

In the next step c5, a straight line course is created which connects the current position of the aircraft to the selected landing point with a straight line. In step c6, a normal numerical calculation based on the straight line distance and the glide ratio is used to calculate the windless altitude H0 required to fly the straight course under the completely windless condition.

In step c7, the correction amount ΔH for the weather conditions, especially the wind direction and wind speed around the aircraft is accumulated by using fuzzy inference. As shown in the following example, there are nine fuzzy control rules in total.

(31) if Course length is long and head wind is strong then
ΔH is large (32) if the course length is long and the headwind is weak then
ΔH is medium (33) if the course length is long and there is no wind then
ΔH is small (34) if the course length is long and there is a tailwind then
ΔH is zero (35) if course length is short and head wind is strong then
ΔH is medium (36) if course length is short and head wind is weak then
ΔH is small (37) if the course length is short and there is no wind then
ΔH is zero (38) if the course length is short and there is a tailwind then
ΔH is zero (39) if the approach direction is the crosswind direction then
ΔH is medium In the next step c8, the obtained windless altitude H0 and the correction amount ΔH are fuzzy added to obtain the altitude required to fly from the current position of the aircraft to the landing point (including uncertainties during flight). Altitude) is obtained as a membership function as shown in FIG. Next, in step c9, the obtained membership function is defuzzified by calculating, for example, the barycentric coordinates, and the grade distribution function is converted into one numerical value H1. Next, in step c10,
Compare the converted numerical value H1 with the current altitude HC of your machine,
If H1 ≦ HC, that is, if the altitude of the aircraft is higher than the converted value H1, the fact that the landing point can be reached is displayed on the screen of the CRT instrument 9. Conversely, if H1> HC, that is, if the altitude of the aircraft is lower than the converted numerical value H1, the fact that the landing point cannot be reached is displayed on the screen of the CRT instrument 9, and the process ends at step c11.

In this way, since the altitude margin calculation can be performed by taking into consideration the uncertain factors that occur during the flight from the current position to the landing point, it is possible to select an accurate and safe emergency landing flight course.

[0040]

As described in detail above, according to the present invention, when the aircraft is out of order, the pilot can predict in advance the flight course at the time of the emergency landing, and by only performing the landing flight according to the best course. Safe and reliable landing is possible. Therefore, the burden on the pilot's decision making can be reduced.

By evaluating the altitude of the aircraft using fuzzy reasoning, it is possible to safely and accurately predict the flight possibility up to the landing possible point in case of an emergency landing.

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of a pilot landing support system according to an embodiment of the present invention.

FIG. 2 is a flowchart showing an operation example of the pilot landing support device shown in FIG.

FIG. 3 is an example of an engine failure warning display.

FIG. 4 is an example of a screen display of landing points.

FIG. 5 (a) is a flowchart showing an example of a course creation method from the position of the aircraft to the landing point.
(B) is a figure which shows the following waypoint selection method,
FIG. 5C is a diagram showing a setting example of each course from the current position to the landing candidate points A and B.

6 (a) to 6 (e) are membership functions used when the pilot landing assistance device according to the present invention executes fuzzy inference, and FIGS. 6 (f) to 6 (r) are It is a fuzzy set regarding the quality of the course.

FIG. 7 is an example of a screen display of a recommended flight course.

8 (a) is a flowchart showing another operation example of the pilot landing support device shown in FIG.
(B) is an example of a membership function obtained by fuzzy addition of the windless altitude H0 and the correction amount ΔH.

[Explanation of symbols]

 1 Pilot landing support device 2 Flight course calculation unit 3 Map generator 4 Display processing unit 5 Engine monitor 6 Navigation sensor 7 Course selection processing unit 8 Input processing unit 9 CRT instrument 10 Touch panel sensor 11 Weather sensor 20 Own machine symbol 21 Engine failure emergency symbol 22 Lifting rate meter 23 Azimuth meter 24 Altitude meter 25 Instrument indicated speed meter 26 Rotor speed meter 27 Landing point selection symbol 28, 29 Landing candidate symbol 30 Reachable range mark 31, 32, 33 Course 35 Landing point symbol 36 Landing point Direction symbol 40 mountain 90 pilot

Claims (2)

[Claims] 1. A self-position detecting means for detecting a self-position, a self-state detecting means for detecting a self-state, a map information storage means for storing map information, and For displaying the position of the self-vehicle, the state of the self-vehicle, and a map around the self-vehicle on the screen based on the signal from the machine position detection means, the signal from the self-vehicle state detection means and the signal from the map information storage means In a pilot landing support device comprising a display means, in the case where there is a failure of the aircraft, flight course creating means for creating a flight course from the position of the aircraft to the landing possible point, and when there are a plurality of flight courses And a flight course evaluation means for determining the best flight course using fuzzy inference. 2. A course length calculating means for calculating a course length from a position of the own aircraft to a landing point, a weather condition detecting means for detecting a weather condition around the own aircraft, and the course length calculating means. 2. The pilot landing according to claim 1, further comprising: own-altitude evaluation means for evaluating the own-altitude using fuzzy inference based on the signal from the vehicle and the signal from the weather condition detecting means. Support device.