Aircraft flight navigation assistance method, flight navigation assistance program, and flight navigation assistance system

Abstract

This aircraft flight navigation assistance method comprises: acquiring flight specification data including the position and attitude of the own aircraft in flight; acquiring point cloud data indicating information relating to the relative distance and relative azimuth from the own aircraft in flight to an object, the relative distance and relative azimuth being detected by a LiDAR sensor; calculating the relative relationship between the aircraft in flight and the object on the basis of the flight specification data and the point cloud data; and outputting the calculated relative relationship information.

Description

Aircraft flight navigation support method, flight navigation support program, and flight navigation support system

[0001] The present disclosure relates to an aircraft flight navigation support method, a flight navigation support control program, and a flight navigation support apparatus.

[0002] Patent Document 1 discloses an apparatus equipped with a flight computer that performs automatic pilot control of an aircraft. The flight computer controls actuators that drive the control surfaces and the like of the aircraft, based on the position, attitude and speed of the aircraft obtained from GPS satellites and attitude sensors.

[0003] Japanese Unexamined Patent Publication No. 2005-8059

[0004] In the apparatus disclosed in Patent Document 1, the aircraft is guided to fly along a predetermined flight path based on the position, attitude and speed of the aircraft. Therefore, the apparatus cannot allow the aircraft to fly in consideration of surrounding objects.

[0005] An aspect of the present disclosure aims to support flight navigation of an aircraft according to the relationship between the aircraft in flight and objects located in the airspace around the aircraft.

[0006] An aircraft flight navigation support method according to an aspect of the present disclosure acquires flight parameter data indicating flight parameters including the own position and own attitude of an aircraft in flight, acquires point cloud data detected by a LiDAR sensor and indicating information related to the relative distance from the aircraft in flight to the object, calculates the relative relationship between the aircraft in flight and the object based on the flight parameter data and the point cloud data, and outputs relative relationship information indicating the calculated relative relationship.

[0007] An aircraft flight navigation support program according to an aspect of the present disclosure causes at least one processor to execute the flight support method. The program may be stored in a computer-readable, non-transitory and tangible storage medium.

[0008] An aircraft flight navigation support system according to one aspect of the present disclosure includes: a laser ranging sensor that scans the space around an aircraft in flight with laser light and receives reflected light from an object in the space to detect the relative distance to the object and outputs data related to the relative distance; and a processing circuit that calculates the relative relationship between the aircraft in flight and the object based on the data and controls an actuator that changes the flight behavior of the aircraft based on the calculated relative relationship.

[0009] According to one aspect of this disclosure, it is possible to support aircraft flight navigation that takes into account objects in the airspace surrounding the aircraft.

[0010] Figure 1 is a block diagram of an aircraft according to an embodiment. Figure 2 is a hardware configuration diagram of the flight control computer in Figure 1. Figure 3 is a block diagram of the flight parameters calculation unit of the flight control system in Figure 1. Figure 4 is a block diagram of the relative relationship calculation unit of the flight control system in Figure 1. Figure 5 is a schematic diagram showing one light-receiving point of point cloud data acquired from a LiDAR sensor by the representative measurement point extraction unit. Figure 6 is a schematic diagram showing point cloud data for a spherical object. Figure 7 is a schematic diagram showing representative light-receiving point data for a spherical object. Figure 8 is a schematic diagram showing the time change of representative light-receiving point data. Figure 9 is a block diagram of a modified example of the relative relationship calculation unit in Figure 4. Figure 10 is a diagram illustrating collision avoidance control of the aircraft in Figure 1. Figure 11 is a diagram illustrating the first guidance control of the aircraft in Figure 1. Figure 12 is a diagram illustrating the second guidance control of the aircraft in Figure 1. Figure 13 is a flowchart illustrating a flight navigation support method for an aircraft.

[0011] The embodiments will be described below with reference to the drawings. Figure 1 is a block diagram of the aircraft 1 according to the embodiment. As shown in Figure 1, the aircraft 1 is equipped with a flight navigation support system 10 that assists the aircraft's flight navigation while taking into account objects in the surrounding airspace. The aircraft 1 of this embodiment is an autonomously flying unmanned aerial vehicle.

[0012] As shown in Figure 10, the aircraft 1 of this embodiment comprises a fuselage 1a, main wings 1b projecting laterally from the central part of the fuselage 1a, horizontal stabilizers 1c projecting laterally from the rear end of the fuselage 1a, vertical stabilizers 1d projecting upward from the rear end of the fuselage 1a, and a propulsion propeller 1e provided on the front end of the fuselage 1a or on the main wings 1b. The main wings 1b are fixed wings.

[0013] Aircraft 1 lifts off the ground due to the lift generated by the air passing along its wings 1b during flight. Therefore, aircraft 1 needs to fly in the direction of propulsion to obtain lift. Consequently, aircraft 1 has a higher minimum speed in the direction of propulsion required to maintain its flight characteristics compared to a rotary-wing aircraft. Aircraft 1 is equipped with a propulsion source 11 that drives a propulsion propeller 1e to generate thrust for aircraft 1. The propulsion source 11 may be an internal combustion engine or an electric motor. The propulsion source 11 adjusts the rotational speed of the propulsion propeller 1e by changing its output torque and the rotational speed of its output shaft. In other words, the propulsion source 11 sets and adjusts the flight speed in the direction of propulsion. The propulsion source 11 is shown in Figure 1.

[0014] As shown in Figure 1, the aircraft 1 is equipped with actuators that change the flight state of the aircraft 1. In this embodiment, the aircraft 1 is equipped with a rudder actuator 12, an aileron actuator 13, and an elevator actuator 14. The rudder actuator 12 drives the movable wing surface of the vertical stabilizer 1d, which adjusts the yaw movement of the aircraft 1. The aileron actuator 13 drives the movable wing surface of the main wing 1b, which adjusts the roll movement of the aircraft 1. The elevator actuator 14 drives the movable wing surface of the horizontal stabilizer 1c, which adjusts the pitch movement of the aircraft 1.

[0015] The propulsion source 11, rudder actuator 12, aileron actuator 13, and elevator actuator 14 are examples of actuators that change the flight state of the aircraft 1.

[0016] The aircraft 1 is equipped with a flight navigation support system 10. The flight navigation support system 10 in this embodiment outputs command signals to drive actuators 11 to 14 for the autonomous flight of the aircraft 1. The flight navigation support system 10 includes an inertial sensor 21, a satellite positioning sensor 22, a LiDAR sensor 23, a clock synchronization control circuit 24, a flight control computer 25, and a drive controller 26.

[0017] The inertial sensor 21 comprises a three-axis accelerometer 31, a gyroscope 32, and a clock oscillator 33. The inertial sensor 21 is an example of a flight parameters sensor. The accelerometer 31 detects the X-axis acceleration ax, Y-axis acceleration ay, and Z-axis acceleration az in the coordinate system of the inertial sensor 21. The inertial sensor 21 detects motion data that includes acceleration components corresponding to inertial force and gravity. The gyroscope 32 detects the angular velocity p around the X axis, the angular velocity q around the Y axis, and the angular velocity r around the Z axis in the coordinate system of the inertial sensor 21. The clock oscillator 33 generates a clock signal of a constant frequency so that the accelerometer 31 and the gyroscope 32 can perform detection operations in synchronization with each other at a constant sampling frequency. That is, the inertial sensor 21 outputs the acceleration ax, ay, az and angular velocities p, q, r as detection data, along with the corresponding clock signal.

[0018] The inertial sensor 21 is mounted on the airframe of aircraft 1. By extracting the direction in which gravity is generated, the inertial sensor 21 can detect information representing the aircraft's 3-axis acceleration, angular velocity around the 3 axes, and attitude around the 3 axes in a gravity coordinate system. Thus, the inertial sensor 21 is a sensor for detecting the aircraft's 3-axis acceleration, angular velocity around the 3 axes, and attitude around the 3 axes in a gravity coordinate system. The measurement period of the inertial sensor 21 is set to be shorter than that of the satellite positioning sensor 22. This allows the measurement data from the inertial sensor 21 to interpolate the discrete motion state of the aircraft obtained from the measurement data of the satellite positioning sensor 22, thereby improving the accuracy of the obtained flight parameters.

[0019] The satellite positioning sensor 22 includes a coordinate receiving circuit 41 and a time receiving circuit 42. The satellite positioning sensor 22 is an example of a flight parameters sensor. The coordinate receiving circuit 41 receives radio waves transmitted from artificial satellites using satellite positioning systems such as the Global Navigation Satellite System (GNSS) and the Quasi-Zenith Satellite System, and measures the position of the satellite positioning sensor 22 in an absolute coordinate system. The satellite positioning sensor 22 is mounted on the airframe of the aircraft 1. The satellite positioning sensor 22 is implemented as a sensor for detecting the position of the aircraft in an absolute coordinate system expressed in latitude, longitude, and altitude.

[0020] The time receiving circuit 42 acquires a clock signal representing the reference time each time it receives a signal based on radio waves transmitted from an artificial satellite. The reference time is information about the time set on the satellite. The reference time may also be information about Coordinated Universal Time (UTC). The satellite positioning sensor 22 outputs positioning data as detection data, along with the corresponding clock signal. The satellite positioning sensor 22 outputs positioning data synchronized with the acquisition time. The satellite positioning sensor 22 outputs positioning data for each acquisition time in a time series as time progresses. The satellite positioning sensor 22 outputs the clock signal acquired by the time receiving circuit 42 to the clock synchronization control circuit 24, which will be described later, as a synchronization signal for synchronizing with other sensor outputs.

[0021] The LiDAR sensor 23 is an example of a laser rangefinder. A laser rangefinder uses laser light to detect objects that are far from the sensor. The laser light emitted from the laser rangefinder uses electromagnetic waves with a much shorter wavelength than the electromagnetic waves used as radar waves. For example, laser light typically uses electromagnetic waves in the ultraviolet, visible light, or near-infrared wavelength range. The LiDAR sensor 23 detects the relative distance to an object by irradiating an object in the airspace surrounding the aircraft 1 with laser light and measuring the time it takes for the reflected light to return. LiDAR is an abbreviation for Light Detection and Ranging. The LiDAR sensor 23 comprises a laser light source 51, a scanning mechanism 52, a light receiving sensor 53, a signal processing circuit 54, and a clock oscillator 55.

[0022] The laser light source 51 emits laser light in pulses, for example. The scanning mechanism 52 rotates a mirror or prism with an electric motor to change the direction of the laser light from the laser light source 51. By rotating the mirror or prism 360°, the scanning mechanism 52 can scan the laser light over a 360° range. The light receiving sensor 53 receives reflected light from the object.

[0023] The signal processing circuit 54 calculates the relative distance from the LiDAR sensor 23 to the object based on the elapsed time from the time the laser light source 51 emits laser light to the time the light receiving sensor 53 receives reflected light. The signal processing circuit 54 calculates angular information indicating the relative angle of the position where the object is located relative to the LiDAR sensor 23, based on the irradiation angle of the laser light acquired from the scanning mechanism 52. The angular information may include the horizontal azimuth angle and the vertical elevation angle.

[0024] The clock oscillator 55 generates a clock signal of a constant frequency to synchronize the laser light source 51, the scanning mechanism 52, and the light receiving sensor 53 with each other. The LiDAR sensor 23 outputs point cloud data, which includes information indicating the relative distance and relative angle from the LiDAR sensor 23 to the object, as detection data along with the corresponding clock signal. For example, the point cloud data is generated as measurement point data from which data indicating the relative distance to the object can be extracted for each laser irradiation direction and laser irradiation time.

[0025] The clock synchronization control circuit 24 synchronizes the detection timing of the flight parameters sensors 21 and 22 and the LiDAR sensor 23. In this embodiment, the clock synchronization control circuit 24 outputs a synchronization signal to synchronize the detection timing of the inertial sensor 21, the satellite positioning sensor 22, and the LiDAR sensor 23. The clock synchronization control circuit 24 outputs the generated synchronization signal to the clock oscillators 33 and 55 of the inertial sensor 21 and the LiDAR sensor 23, respectively. For example, the inertial sensor 21 and the LiDAR sensor 23 may include the synchronization signal in the clock signal they output.

[0026] This allows the clock signals, including the synchronization signals output from each of the sensors 21, 22, and 23, to be compared, thereby arranging the acquired data from each sensor 21, 22, and 23 on a synchronized time axis. In this way, the clock synchronization control circuit 24 controls the clock signal of the satellite positioning sensor 22, the clock oscillator 33 of the inertial sensor 21, and the clock oscillator 55 of the LiDAR sensor 23 to synchronize with each other. When the timestamps of the clock signals included in the output signals of the inertial sensor 21, satellite positioning sensor 22, and LiDAR sensor 23 are the same, the detection data included in those output signals is data acquired at the same time.

[0027] The flight control computer 25 includes a flight parameters calculation unit 61, a planned flight path storage unit 62, a flight management storage unit 63, a rudder angle-thrust command calculation unit 64, a relative relationship calculation unit 65, and a correction unit 66.

[0028] Figure 2 is a hardware configuration diagram of the flight control computer 25 shown in Figure 1. As shown in Figure 2, the flight control computer 25 includes a processor 111, system memory 112, storage memory 113, and interface 115. The processor 111 may include a CPU. The system memory 112 may include volatile memory such as RAM. The storage memory 113 may include non-volatile memory such as a hard disk, non-volatile memory, or a combination thereof. The storage memory 113 stores the control program 114. The control program 114 corresponds to the flight navigation support program.

[0029] One example of a processing circuit 110 is a configuration in which the processor 111 executes a control program 114 read from the storage memory 113 into the system memory 112. The processing circuit 110 includes the processor 111, the system memory 112, and the storage memory 113 that stores the control program 114.

[0030] As shown in Figures 1 and 2, the processor 111 that executes the control program 114 functions as a flight parameters calculation unit 61, a rudder angle-thrust command calculation unit 64, a relative relationship calculation unit 65, and a correction unit 66. The storage memory 113 functions as a planned flight path storage unit 62 and a flight management storage unit 63.

[0031] As shown in Figure 1, the flight parameters calculation unit 61 calculates the flight parameters of the aircraft 1 in an absolute coordinate system based on signals acquired from the inertial sensor 21 and the satellite positioning sensor 22. The flight parameters of the aircraft 1 include, for example, the position of the aircraft 1 (longitude, latitude, and altitude), the velocity vector V1 of the aircraft 1, and the attitude of the aircraft 1. The velocity vector V1 is a three-dimensional vector in the absolute coordinate system. The attitude is the attitude around three axes in the absolute coordinate system. The absolute coordinate system is a coordinate system whose origin is located away from the aircraft 1 and does not affect the motion of the aircraft 1.

[0032] The flight parameters calculation unit 61 calculates the flight distance and flight direction of the aircraft 1 based on the acceleration continuously received from the inertial sensor 21, and can estimate the position of the aircraft 1 (longitude, latitude, and altitude) in absolute coordinates. The flight parameters calculation unit 61 can correct the estimated position using the position of the aircraft 1 (longitude, latitude, and altitude) in absolute coordinates received from the satellite positioning sensor 22, and calculate the aircraft's own position, which is the position of the aircraft 1 in absolute coordinates. The flight parameters calculation unit 61 may use positioning data from the satellite positioning sensor 22 as the initial state for calculating the position of the aircraft 1. The flight parameters calculation unit 61 may update the position of the aircraft 1 with positioning data each time it receives positioning data from the satellite positioning sensor 22.

[0033] The planned flight path memory unit 62 stores the planned flight path of the aircraft 1, which is determined according to a predetermined flight plan. The planned flight path includes the final destination and several waypoints from the current location to the final destination. The planned flight path may be provided from outside the flight control computer 25, or it may be determined by the flight control computer 25 through internal calculations.

[0034] The flight management memory unit 63 stores a predetermined flight pattern in which the aircraft 1 flies so as to be guided toward an object. The flight pattern may be, for example, a group control pattern in which the aircraft 1 follows other aircraft 2 while maintaining a predetermined relative positional relationship with other aircraft 2, or an approach pattern in which the aircraft 1 flies toward an object so as to approach the object. Note that either the planned flight path memory unit 62 or the flight management memory unit 63 may be omitted.

[0035] The rudder angle-thrust command calculation unit 64 calculates command values ​​for the thrust and rudder angle of the aircraft 1 based on flight parameter data obtained from the flight parameter calculation unit 61, for example, so that the aircraft 1 flies at a predetermined speed along a planned flight path stored in the planned flight path memory unit 62. The drive controller 26 controls the propulsion source 11, rudder actuator 12, aileron actuator 13, and elevator actuator 14 to realize the thrust and rudder angle calculated by the rudder angle-thrust command calculation unit 64. Based on the command values, the drive controller 26 calculates the required driving force for each actuator 12 to 14 and controls each actuator 12 to 14. Each actuator 12 to 14 may be driven by electric power, hydraulics, or pneumatics.

[0036] The relative relationship calculation unit 65 calculates the relative relationship between an aircraft 1 in flight and an object present in the airspace surrounding the aircraft 1. In this embodiment, the relative relationship calculation unit 65 calculates the relative relationship based on point cloud data acquired from the LiDAR sensor 23 and flight parameter data acquired from the flight parameter calculation unit 61. The relative relationship calculation unit 65 can calculate the relative relationship by extracting point cloud data and flight parameter data whose acquisition times are synchronized with each other, based on synchronized clock signals. Clock signals controlled by the clock synchronization control circuit 24 and oscillated at the same time are used as synchronization information. Synchronization information is information used to synchronize the flight parameter data and point cloud data according to the detection timing. Synchronization information is information used to synchronize the acquisition timing of each detection value by multiple sensors. The object is, for example, another aircraft 2 flying in the airspace surrounding aircraft 1, as shown in Figure 10.

[0037] The relative relationship includes, for example, the relative distance between aircraft 1 and other aircraft 2, the relative angle of the position of other aircraft 2 with respect to aircraft 1, and the relative velocity of other aircraft 2 with respect to aircraft 1. The relative angle is, for example, the angle between the heading of aircraft 1 and the direction of the position of other aircraft 2 as seen from the position of aircraft 1.

[0038] The relative relationship calculation unit 65 outputs relative relationship information indicating the calculated relative relationship to the correction unit 66. Based on the relative relationship calculated by the relative relationship calculation unit 65, the correction unit 66 corrects the thrust and rudder angle commands of aircraft 1 so that the relative distance between aircraft 1 and other aircraft 2 is maintained at or above a predetermined control interval.

[0039] Figure 3 is a block diagram of the flight parameters calculation unit 61 of the flight navigation support system 10 shown in Figure 1. As shown in Figure 3, the flight parameters calculation unit 61 outputs flight parameters data showing the flight parameters of the aircraft 1. Here, the aircraft's flight parameters include absolute position, absolute speed, and absolute attitude. The flight parameters calculation unit 61 may perform a known navigation method, which is a composite navigation method using the inertial sensor 21 and the satellite positioning sensor 22. The flight parameters calculation unit 61 includes a coordinate transformation unit 71, a speed calculation unit 72, a position calculation unit 73, a coordinate transformation unit 74, an attitude angle calculation unit 75, and an estimation unit 76.

[0040] The estimation unit 76 estimates the current motion state of the aircraft 1 based on cumulative data continuously acquired during flight in a flight state with temporal deviation. Specifically, the estimation unit 76 estimates the future motion state if the past motion state is continued, based on the equation of motion for the state. The estimation unit 76 estimates the current position of the aircraft 1 in the absolute coordinate system based on past positioning data and past motion states. For example, the estimation unit 76 takes the past position of the aircraft 1, the past inertial velocity and inertial position of the aircraft 1 as input, performs state estimation processing, and outputs the current acceleration, angular velocity, and position of the aircraft 1 in the absolute coordinate system as estimated values.

[0041] The estimation unit 76 receives positioning data from the satellite positioning sensor 22 as past position. The estimation unit 76 receives velocity data from the velocity calculation unit 72 and position data from the position calculation unit 73 as past motion state. The estimation unit 76 outputs estimated motion state data to the acceleration coordinate transformation unit 71, velocity calculation unit 72, position calculation unit 73, angular velocity coordinate transformation unit 74, and attitude angle calculation unit 75.

[0042] The state estimation process executed by the estimation unit 76 can use a known state estimation model that estimates the state of a target object from observation data. The position of the aircraft 1 in the absolute coordinate system may be referred to as the absolute position of the aircraft 1. In the present embodiment, the estimation unit 76 is implemented using a Kalman filter. By using the estimation unit 76, even when the positioning data acquired from the satellite positioning sensor 22 contains noise, or when the positioning data is discrete with respect to time, the motion state of the aircraft 1 can be accurately estimated by the estimation unit 76.

[0043] The coordinate conversion unit 71 refers to the absolute position and absolute attitude of the aircraft 1 estimated by the estimation unit 76, and converts the accelerations ax, ay, az in the sensor coordinate system acquired from the inertial sensor 21 into accelerations in the absolute coordinate system. For example, the coordinate conversion unit 71 corrects the acceleration calculated based on the information provided from the acceleration sensor 31, based on the estimation information such as the acceleration provided from the estimation unit 76.

[0044] The speed calculation unit 72 integrates the acceleration calculated by the coordinate conversion unit 71 to calculate the speed of the aircraft 1 in the absolute coordinate system. The speed of the aircraft 1 in the absolute coordinate system may be referred to as the absolute speed of the aircraft 1. The absolute speed of the aircraft 1 is a speed vector including three-axis speed components Vn, Ve, Vd. The speed calculation unit 72 corrects the speed calculated based on the information provided from the coordinate conversion unit 71, based on the estimation information such as the speed provided from the estimation unit 76.

[0045] The position calculation unit 73 integrates the speed calculated by the speed calculation unit 72 to calculate the current position of the aircraft 1 in the absolute coordinate system. The position calculation unit 73 corrects the position calculated based on the information provided from the speed calculation unit 72, based on the estimation information such as the position provided from the estimation unit 76.

[0046] The coordinate conversion unit 74 refers to the absolute position and absolute attitude of the aircraft 1 estimated by the estimation unit 76, and converts the angular velocities p, q, r in the sensor coordinate system acquired from the inertial sensor 21 into angular velocities in the absolute coordinate system. The coordinate conversion unit 74 corrects the angular velocity calculated based on the information provided from the gyro sensor 32, based on the estimation information such as the acceleration provided from the estimation unit 76.

[0047] The attitude angle calculation unit 75 integrates the angular velocity calculated by the coordinate transformation unit 74 to calculate the attitude angle of the aircraft 1 in the absolute coordinate system. The attitude angle of the aircraft 1 in the absolute coordinate system may be referred to as the absolute attitude of the aircraft 1. The attitude angle calculation unit 75 corrects the attitude angle calculated based on the information provided from the coordinate transformation unit 74, on the basis of estimation information such as the attitude angle provided from the estimation unit 76.

[0048] FIG. 4 is a block diagram of the relative relationship calculation unit 65 of the flight navigation support system 10 in FIG. 1. The relative relationship calculation unit 65 calculates the relative relationship between the flying aircraft 1 and an object on the basis of flight specification data and point cloud data. The relative relationship calculation unit 65 includes a representative measurement point extraction unit 81, a coordinate transformation unit 82, a velocity calculation unit 83, a coordinate transformation unit 84, and an estimation unit 85.

[0049] The representative measurement point extraction unit 81 extracts representative light receiving point data as representative measurement point data indicating the position of another aircraft 2 that is an object, on the basis of point cloud data acquired from the LiDAR sensor 23. In other words, the representative measurement point extraction unit 81 calculates the relative distance from the aircraft 1 to the other aircraft 2 and the relative angle of the position of the other aircraft 2 with the aircraft 1 as a reference. In the present embodiment, the representative measurement point extraction unit 81 outputs information based on the sensor coordinate system from the LiDAR sensor 23.

[0050] Figure 5 schematically shows one of the point cloud data acquired by the representative measurement point extraction unit 81 from the LiDAR 23 sensor. The representative measurement point extraction unit 81 labels the pixel reflected at the shortest distance from the point cloud data as the representative light receiving point P, which is representative of the object. For example, a three-dimensional coordinate system with the sensor position as the origin O is used as the sensor coordinate system of the LiDAR sensor 23. For example, the position P of the object is expressed by three things: the height position h with respect to the XY plane, the circumferential position λ with respect to the X axis, and the distance r from the origin O to the object. In this case, the height position h of the object is set to the position in the direction in which the rotation axis of the laser beam extends. The circumferential position λ is set to the position in the circumferential direction around the rotation axis of the laser beam. The distance r from the origin O to the object is set to the distance of the straight line connecting the sensor position O to the object position P. The sensor coordinate system only needs to be given information that represents the three-dimensional position, and the above representation is just one example; other representations may also be used.

[0051] Figure 6 schematically shows point cloud data for a spherical object. In Figure 6, the position of the point cloud data is shown in a coordinate system in which the height position h and circumferential position λ are arranged vertically and horizontally on a two-dimensional graph. In Figure 6, the distance from the origin to the object is represented by the density of the points. The denser the point, the closer the distance from the laser irradiation point to the object. Image processing is performed so that the point corresponding to the nearest point to the sensor becomes denser, and the point becomes fainter as it moves away from the nearest point in the height and circumferential directions. In this way, the LiDAR sensor 23 outputs image information that shows the relative position of each part of the object in three-dimensional space in the sensor coordinate system. In this embodiment, height position h, circumferential position λ, and distance r information were used to represent the position information of each part of the object, but the position information may also be output in polar coordinates or Cartesian coordinates.

[0052] The LiDAR sensor 23 periodically emits laser light over time. Specifically, when the LiDAR sensor 23 emits laser light in a 360-degree circle, it outputs the position information of the object based on the laser light emitted in the first circle t1 and the position information of the object based on the laser light emitted in the second circle t2 in a distinguishable manner. In this way, the LiDAR sensor 23 generates position information for each rotation of the laser light. As a result, the point cloud data is generated as data that can be extracted for each laser irradiation direction and laser irradiation time, showing the relative distance from the LiDAR sensor 23 to the object.

[0053] When the LiDAR sensor 23 is mounted on aircraft 1, the point cloud data output by the LiDAR sensor 23 includes multiple point data indicating the relative distances from the LiDAR sensor 23 to multiple parts on the outer surface of other aircraft 2. The representative measurement point extraction unit 81 extracts one representative light-receiving point data from the point cloud data acquired from the LiDAR sensor 23, according to predetermined rules, which represents the relative position and relative distance from aircraft 1 to other aircraft 2.

[0054] Figure 7 schematically shows representative light-receiving point data P1 for a spherical object. For example, the representative measurement point extraction unit 81 labels and extracts the point data having distance information indicating the shortest relative distance from the point cloud data as representative light-receiving point data P1 at the pixel level. The representative light-receiving point data P1 represents the relative position and relative distance from aircraft 1 to other aircraft 2. The representative light-receiving point data P1 is extracted as the representative light-receiving point corresponding to the laser light emitted by the LiDAR sensor 23 for the nth time. The representative light-receiving point data P1 includes a clock signal, which is information that enables synchronization with other sensors 21 and 22. In this embodiment, the relative relationship calculation unit 65 utilizes the representative light-receiving point data P1 extracted by the representative measurement point extraction unit 81 from the point cloud data from the LiDAR sensor 23 as flight navigation support data.

[0055] Figure 8 schematically shows the time change of representative light receiving point data. The representative measurement point extraction unit 81 may collect the extracted representative light receiving point data P1 for each laser light irradiation time. The representative measurement point extraction unit 81 may output the relative position change of the object by calculating and outputting the time change of the collected representative light receiving point data P1. For example, as shown in Figure 8, the relative height change amount Δh, the relative circumferential change amount Δλ, and the relative distance change amount Δr of the object are estimated by calculating the deviation in the time change of the representative light receiving point data P1, P2, and P3. In this way, the representative measurement point extraction unit 91 may output information regarding the time change of the representative light receiving point using past representative light receiving point data in addition to the position information of the representative light receiving point.

[0056] Returning to Figure 4, the coordinate transformation unit 82 calculates the position of the other aircraft 2 in the absolute coordinate system based on the representative light receiving point data P1 information obtained from the representative measurement point extraction unit 81 and the flight parameters data obtained from the flight parameters calculation unit 61 shown in Figure 3. Specifically, the coordinate transformation unit 82 compares the clock signal of the representative light receiving point data P1 with the clock signal of the flight parameters data to obtain information including the position and attitude of the aircraft 1 in the absolute coordinate system at the time the laser light was emitted. The coordinate transformation unit 82 reads out a transformation formula for converting the sensor coordinate system to the absolute coordinate system. Based on the read-out transformation formula, the coordinate transformation unit 82 calculates the three-dimensional position of the representative light receiving point data P1 in the absolute coordinate system.

[0057] The estimation unit 85 estimates the current motion state of the object in the absolute coordinate system based on its past motion state. Specifically, the estimation unit 85 estimates the future motion state of the other aircraft 2 if the past motion state continues, based on the equation of motion for the state. The estimation unit 85 estimates the current position of the other aircraft 2 in the absolute coordinate system based on the past position of the other aircraft 2 calculated by the coordinate transformation unit 82 and its past motion state. For example, the estimation unit 85 takes the past position of the other aircraft 2, its past inertial velocity, and inertial position as input, performs a state estimation process, and outputs the current angular velocity and position of the other aircraft 2 in the absolute coordinate system as estimated values.

[0058] The estimation unit 85 receives the position of the representative light receiving point P1 and the position of the other aircraft 2 from the coordinate transformation unit 82 as inputs, representing the past position of the other aircraft 2. The estimation unit 85 also receives velocity data from the velocity calculation unit 83 as inputs, representing the past motion state of the other aircraft 2.

[0059] The estimation unit 85 outputs estimated motion state data to the coordinate transformation unit 82 and the velocity calculation unit 83. The state estimation process performed by the estimation unit 85 can use a known state estimation model that estimates the state of an object from observation data. In this embodiment, the estimation unit 85 may output acceleration data as the motion state of the other aircraft 2 by differentiating the velocity data given by the velocity calculation unit 83. The estimation unit 85 may correct the flight parameters of the other aircraft 2 based on information indicating the flight parameters of aircraft 1 from the flight parameters calculation unit 61. This allows the estimation unit 85 to output the flight parameters of the other aircraft 2 while suppressing the influence of the motion of aircraft 1 included in the point cloud data.

[0060] In this embodiment, the estimation unit 85 is implemented using a Kalman filter. By using the estimation unit 85, the flight parameters of the other aircraft 2 can be accurately estimated by the estimation unit 85 even when the point data acquired from the LiDAR sensor 23 contains noise, or when the positioning data acquired from the LiDAR sensor 23 is discrete with respect to time.

[0061] The coordinate transformation unit 82 refers to the position of the other aircraft 2 estimated by the estimation unit 85 and converts the position of the representative light-receiving point data P1 obtained from the representative measurement point extraction unit 81 into a position in the absolute coordinate system. For example, the coordinate transformation unit 82 corrects the position of the other aircraft 2 calculated based on the representative light-receiving point data P1 based on estimated information such as the position of the other aircraft 2 provided by the estimation unit 85. The output period of the representative light-receiving point data P1 corresponds to the time it takes for the laser light from the LiDAR sensor 23 to complete one revolution around the rotation axis. The position of the other aircraft 2 during the time between outputting the representative light-receiving point data P1 and outputting the next representative light-receiving point data P2 can be interpolated based on the information obtained from the estimation unit 85. This allows the coordinate transformation unit 82 to increase the frequency of outputting the position information of the other aircraft 2 per unit time. In this way, the coordinate transformation unit 82 can output the position information of the other aircraft 2 more times than the number of times the representative light-receiving point data is output. In other words, by including the estimation unit 85, information estimating the position of other aircraft 2 can be output at time intervals shorter than the measurement cycle of the LiDAR sensor 23, thereby increasing the frequency of flight support for aircraft 1 based on other aircraft 2.

[0062] The velocity calculation unit 83 calculates the velocity of the other aircraft 2 in the absolute coordinate system by differentiating the position data of the other aircraft 2, which is sequentially acquired from the coordinate transformation unit 82 over time. Specifically, the velocity calculation unit 83 calculates the velocity vector V2 of the other aircraft 2 based on the time change of the information indicating the position of the other aircraft 2 given by the coordinate transformation unit 82. That is, the velocity calculation unit 83 calculates the amount of displacement per unit time and the direction of displacement of the other aircraft 2 in the absolute coordinate system as the velocity vector V2 of the other aircraft 2 based on the time-series data of the position of the other aircraft 2 acquired from the coordinate transformation unit 82. The velocity vector V2 is a three-dimensional vector. The velocity calculation unit 83 corrects the velocity calculated based on the position information of the other aircraft 2 given by the coordinate transformation unit 82 and the estimation unit 85 based on estimated information such as velocity and acceleration given by the estimation unit 76.

[0063] The coordinate transformation unit 84 outputs the relative relationship between aircraft 1 and the other aircraft in the gravity coordinate system of aircraft 1. Specifically, the coordinate transformation unit 84 calculates the relative velocity vector Vr between aircraft 1 and the other aircraft 2 based on the velocity vector V2 in the absolute coordinate system of the other aircraft 2 obtained from the velocity calculation unit 83 and the velocity vector V1 in the absolute coordinate system of aircraft 1 obtained from the flight parameters calculation unit 61. The relative velocity vector Vr may be a three-dimensional vector in the gravity coordinate system with aircraft 1 as the reference.

[0064] The coordinate transformation unit 84 calculates the relative distance D between aircraft 1 and other aircraft 2 based on the absolute coordinate system position of other aircraft 2 obtained from the coordinate transformation unit 82 and the absolute coordinate system position of aircraft 1 obtained from the flight parameters calculation unit 61. The coordinate transformation unit 84 calculates the relative angle α of the position of other aircraft 2 in gravity coordinates relative to aircraft 1 based on the absolute coordinate system position of other aircraft 2 obtained from the coordinate transformation unit 82 and the absolute coordinate system position and attitude of aircraft 1 obtained from the flight parameters calculation unit 61. The relative angle α may be the angles α1, α2, and α3 around the three axes of the gravity coordinate system relative to the aircraft. In addition to the position and attitude of aircraft 1, the coordinate transformation unit 84 calculates the relative relationship based on the velocity vector V1 of aircraft 1 and the time change of attitude of aircraft 1 obtained from the flight parameters calculation unit 61. As a result, the coordinate transformation unit 84 can output a relative relationship that takes into account the state change of aircraft 1 in addition to the position change of other aircraft 2, thereby improving the accuracy of the relative relationship estimation.

[0065] Figure 9 is a block diagram of a modified example of the relative relationship calculation unit 65 in Figure 4. Instead of the relative relationship calculation unit 65 in Figure 4, the relative relationship calculation unit 165 of the modified example in Figure 5 may be used. As shown in Figure 9, the relative relationship calculation unit 165 includes a representative measurement point extraction unit 91, a velocity calculation unit 92, and an estimation unit 93.

[0066] The representative measurement point extraction unit 91, similar to the representative measurement point extraction unit 81, calculates the relative distance D from aircraft 1 to other aircraft 2 and the relative angle α of the position of other aircraft 2 relative to aircraft 1, based on point cloud data acquired from the LiDAR sensor 23. The estimation unit 93 estimates the current relative distance and relative angle based on the past relative distance and relative angle calculated by the representative measurement point extraction unit 91 and the current relative distance and relative angle calculated by the representative measurement point extraction unit 91. The estimation unit 93 is implemented, for example, using a Kalman filter.

[0067] The velocity calculation unit 92 calculates the relative velocity vector Vr between aircraft 1 and other aircraft 2 based on the time-series data of relative distance and relative angle obtained from the representative measurement point extraction unit 91. Specifically, the velocity calculation unit 92 calculates the amount of deviation of the relative distance per unit time obtained from the representative measurement point extraction unit 91 as a scalar value of the velocity vector Vr, and calculates the amount of deviation of the relative angle per unit time obtained from the representative measurement point extraction unit 91 as the direction of the velocity vector Vr.

[0068] Figure 10 is a diagram illustrating the collision avoidance control algorithm for aircraft 1 in Figure 1. As shown in Figure 10, the object in the airspace surrounding aircraft 1 is, for example, another aircraft 2. The relative relationship calculation unit 65 considers the position of the representative light receiving point P on the outer surface of other aircraft 2, where the relative distance from aircraft 1 to other aircraft 2 detected by the LiDAR sensor 23 is the shortest, as the position of other aircraft 2. Using the data related to the representative light receiving point P, the relative relationship calculation unit 65 calculates the relative distance D from aircraft 1 to other aircraft 2, the relative angle α of the position of other aircraft 2 with respect to aircraft 1, and the relative velocity vector Vr of aircraft 1 with respect to other aircraft 2.

[0069] The correction unit 66 sets a virtual proximity warning area Z around the representative light receiving point P of the other aircraft 2. For example, the proximity warning area Z may be a spherical shape with radius R centered on the representative light receiving point P of the other aircraft 2. The proximity warning area Z may also be a vertically extending cylindrical shape with a circular cross-section centered on the representative light receiving point P of the other aircraft 2. The radius R of the proximity warning area Z may be the control interval, which is the allowable lower limit of the relative distance D between aircraft 1 and the other aircraft 2. The correction unit 66 corrects the thrust and rudder angle commands of aircraft 1 calculated by the rudder angle-thrust command calculation unit 64 so that the relative distance D between aircraft 1 and the other aircraft 2 is kept at or above a predetermined control interval R.

[0070] For example, the correction unit 66 determines whether the relative velocity vector Vr, starting from aircraft 1, is pointing inward into the proximity warning area Z, based on the relationship between the relative velocity vector Vr and the proximity warning area Z. If the correction unit 66 determines that the relative velocity vector Vr is pointing inward into the proximity warning area Z, it corrects the command value of the rudder angle-thrust command calculation unit 64 so that the relative velocity vector Vr points outward from the proximity warning area Z. As a result, the relative distance D will be maintained at or above a predetermined control interval R in the future, and aircraft 1 will be able to avoid a collision with other aircraft 2 through autonomous flight.

[0071] The correction unit 66 may set a predetermined warning zone around the proximity warning area Z. If the correction unit 66 determines that aircraft 1 has entered the warning zone and the relative velocity vector Vr is pointing inward towards the proximity warning area Z, it may correct the command value of the rudder angle-thrust command calculation unit 64 so that the relative velocity vector Vr points outward towards the proximity warning area Z. In other words, if the correction unit 66 determines that the relative distance D between aircraft 1 and other aircraft 2 is less than a predetermined allowable value and the relative velocity vector Vr is pointing inward towards the proximity warning area Z, it may correct the command value of the rudder angle-thrust command calculation unit 64 so that the relative velocity vector Vr points outward towards the proximity warning area Z. As a result, as long as aircraft 1 is far enough away from other aircraft 2, it will not affect the flight of other aircraft 2.

[0072] In this embodiment, another aircraft 2 is used as an example of an object in the airspace surrounding aircraft 1. However, since the LiDAR sensor 23 can detect any object that can reflect laser light, it is possible to increase the number of objects that can be easily detected compared to airborne collision avoidance systems (TCAS) that use transponders and radar waves that use radio waves.

[0073] Figure 11 is a diagram illustrating the first guidance control of aircraft 1 in Figure 1. As shown in Figure 11, the object in the airspace surrounding aircraft 1 is, for example, another aircraft 2. In the first guidance control, the rudder angle-thrust command calculation unit 64 calculates command values ​​for the thrust and rudder angle of aircraft 1 so that aircraft 1 is guided to other aircraft 2 according to the first flight pattern stored in the flight management storage unit 63, while referring to the flight parameter data obtained from the flight parameter calculation unit 61 and the relative relationship obtained from the relative relationship calculation unit 65.

[0074] In the first flight pattern, aircraft 1 flies while forming a predetermined formation with other aircraft 2. That is, in the first flight pattern, aircraft 1 flies such that it has a predetermined relative distance D and relative angle α with respect to other aircraft 2. Aircraft 1 flies such that its relative velocity vector Vr is below a predetermined value near zero, i.e., it has approximately the same velocity vector as other aircraft 2. In this way, aircraft 1 can fly in a manner that follows other aircraft 2.

[0075] Furthermore, when group control is implemented in which another aircraft 2 functions as the control aircraft and aircraft 1 functions as the follow aircraft, aircraft 1 can perform proportional navigation flight based on relative relationship information acquired from the LiDAR sensor 23. Therefore, in situations where detailed flight control is not required, the inertial sensor 21 and satellite positioning sensor 22 can be omitted. Aircraft 1 may also be controlled based on relative relationship information acquired from the LiDAR sensor 23 mounted on the other aircraft 2. In this case, aircraft 1 can also be without the LiDAR sensor 23.

[0076] Figure 12 is a diagram illustrating the second guidance control of the aircraft 1 shown in Figure 1. As shown in Figure 12, the object in the space surrounding the aircraft 1 is, for example, a target object T which is the destination of the aircraft 1, such as an airport. In the second guidance control, the rudder angle-thrust command calculation unit 64 calculates control command values ​​for the thrust and rudder angle of the aircraft 1 so that the aircraft 1 is guided to the target object T according to the second flight pattern stored in the flight management memory unit 63, while referring to the flight parameter data obtained from the flight parameter calculation unit 61 and the relative relationship obtained from the relative relationship calculation unit 65.

[0077] In the second flight pattern, aircraft 1 flies toward target object T. For example, target object T may be an airfield on the ground, or another aircraft to which aircraft 1 docks for refueling, etc. In other words, target object T may be an air station or ground station to which aircraft 1 lands. In the second guidance and control, the rudder angle-thrust command calculation unit 64 calculates control command values ​​for the thrust and rudder angle of aircraft 1 so that aircraft 1 arrives at target object T, while referring to the flight parameter data obtained from the flight parameter calculation unit 61 and the relative relationship obtained from the relative relationship calculation unit 65.

[0078] Figure 13 is a flowchart illustrating the flight navigation support method for the aircraft 1 described above. In this embodiment, the flight navigation support method is implemented by the flight control computer 25 executing a calculation program. When the flight control computer 25 determines that flight navigation support control based on the relative relationship with other aircraft 2 is necessary during flight, it starts flight navigation support control and proceeds to step S1.

[0079] In step S1, the flight control computer 25 acquires flight parameters data indicating the flight status of aircraft 1. The flight control computer 25 acquires information from inertial sensors 21 and satellite positioning sensors 22, etc., to calculate the position, attitude, and their changes over time of aircraft 1. Once the information necessary for calculating the flight parameters has been acquired, the flight control computer 25 proceeds to step S2. In step S2, the flight control computer 25 acquires relative data, including the relative distance and relative angle from aircraft 1 to other aircraft 2, detected by laser ranging sensors such as LiDAR sensors. Once such information regarding the relative relationship of other aircraft 2 has been acquired, the flight control computer 25 proceeds to step S3.

[0080] In step S3, the flight control computer 25 calculates the relative relationship between aircraft 1 in flight and other aircraft 2 based on the data acquired in steps S1 and S2. The data acquired in steps S1 and S2 includes synchronization information that allows the acquisition timing of each data to be compared. This allows the flight control computer 25 to synchronize the detection times of each sensor and accurately calculate the relative relationship based on the data acquired in each step. In particular, even for aircraft 1 flying at high speed to obtain lift to maintain flight, the relative relationship can be calculated while suppressing the effect of detection timing delays between sensors. Once the relative relationship is calculated, the flight control computer 25 proceeds to step S4.

[0081] In step S4, the flight control computer 25 calculates the rudder angle-thrust command values ​​based on the calculated relative relationship, according to a pre-set flight navigation support program. As described above, the flight control computer 25 controls the flight state of aircraft 1 to avoid collision with other aircraft 2, maintain a predetermined relative position with respect to other aircraft 2, or approach target object T.

[0082] In step S5, the flight control computer 25 calculates the required driving force for each actuator based on the command value and controls each actuator. If the flight control computer 25 determines that flight navigation support control based on the relative relationship with other aircraft 2 is unnecessary during flight, it terminates the program. On the other hand, if the flight control computer 25 determines in step S5 that it is necessary to continue flight navigation support control, it returns to step S1 and continues the program.

[0083] The processing steps of the flight control computer 25 described above are generally time-series processing, but they may be processed independently in parallel. Some of the processing of the flight control computer 25 may be performed independently by other entities. For example, a processing circuit or electronic circuit may be provided to independently execute steps S1 to S3.

[0084] In this embodiment, application to unmanned aerial vehicles (UAVs) is disclosed, but it is applicable to manned aircraft, gliders, drones, and other flying objects. Compared to manned aircraft that transport people, UAVs are desirable for simpler equipment, weight limitations on payloads, and reduced equipment costs, and there is a tendency for increased productivity and reduced manufacturing costs to be desired. In this embodiment, a general-purpose laser ranging sensor such as a LiDAR sensor is used. In this case, compared to equipping the aircraft with radar equipment, it is possible to achieve both reduced manufacturing costs and flight navigation support that takes the target object into consideration. As described above, in this embodiment, the flight navigation of the aircraft can be supported by taking into consideration the flight status of the aircraft and other aircraft. This makes it possible to efficiently support the flight navigation of fixed-wing aircraft, which are likely to have high thrust speeds.

[0085] In this embodiment, the data from the closest receiving point is used as the representative receiving point. This eliminates the need to wait for data where the laser light is reflected with a delay, thereby increasing the extraction speed of the representative receiving point data. This enables rapid navigation support control calculations.

[0086] The technology disclosed herein is not limited to the embodiments described above. The output of relative relationship information by the relative relationship calculation unit 65 may be displayed to the operator of aircraft 1 or transmitted to a receiver of another aircraft 2. The object detected by the LiDAR sensor 23 of aircraft 1 may be a fixed object or a moving object.

[0087] The aircraft 1 disclosed herein may be a manned aircraft capable of autonomous flight. In addition to being an aircraft capable of autonomous flight, the aircraft 1 may also be an aircraft capable of human operation. The aircraft 1 may be an aircraft capable of selectively switching between a human-operated flight mode and an autonomous flight mode.

[0088] Aircraft 1 may be a fixed-wing aircraft or a rotary-wing aircraft. Aircraft 1 may have both rotary and fixed wings. If aircraft 1 is a rotary-wing aircraft, aircraft 1 may have one rotor (single-copter) or multiple rotors (multi-copter) for generating lift. Aircraft 1 may be any flying object that propels itself through the air using a propulsion source, and existing structures may be applied to the structure for flight. For example, the propulsion source of aircraft 1 may be a gas turbine engine that generates a jet that imparts thrust to aircraft 1. The actuators described as embodiments are examples, and some of the actuators may be omitted or integrated, and auxiliary actuators may be provided in addition.

[0089] If aircraft 1 is a rotary-wing aircraft having multiple rotors, attitude control in the pitch, roll, and yaw directions may be performed by adjusting the control surface, pitch angle, and rotation speed of each of the multiple rotors.

[0090] The flight control computer 25 is configured as a separate computer from the drive controller 26, but it may include the drive controller 26. The relative relationship calculation unit 65 may be provided separately from the flight control computer 25. In this case, the relative relationship calculation unit 65 may be implemented by including an electrical circuit separate from the processing circuit included in the flight control computer 25. The relative relationship calculation unit 65 may be implemented by including a processing circuit that executes a calculation program for calculating relative relationships, separately from the flight control computer 25. In this case, the relative relationship processing circuit constituting the relative relationship calculation unit 65 acquires flight parameter data and point cloud data, respectively. Based on the acquired information, the relative relationship processing circuit calculates the relative relationship between the aircraft 1 in flight and the object, and outputs the calculated relative relationship information to other electronic equipment such as the flight control computer 25. For example, the relative relationship processing circuit may output relative relationship information to a notification device. In this case, the notification device notifies the relative relationship information, allowing the operator to grasp the relative relationship information.

[0091] In this embodiment, the relative relationship calculation unit 65 is provided on the aircraft 1, but it is sufficient that it can acquire flight parameter data and point cloud data, and it may be provided outside the aircraft 1 equipped with the LiDAR sensor. For example, the relative relationship calculation unit 65 may be implemented by a calculation device provided on an aircraft other than the aircraft 1 equipped with the LiDAR sensor, or by a calculation device provided on ground equipment. For example, if the aircraft 1 is operated or monitored by a human, the calculation device may issue a warning or display instructions to perform collision avoidance support actions when the aircraft 1 reaches a set area around an object or when a relative approach to an object is predicted.

[0092] In this embodiment, it is sufficient to achieve synchronous control of each sensor 21, 22, and 23. For example, the output signals of the other sensors may be synchronized based on a clock signal output from a clock oscillator provided in one of the sensors 21, 22, and 23. Alternatively, the output signals of each sensor 21, 22, and 23 may be synchronized based on a clock signal output from a clock oscillator provided separately from each sensor 21, 22, and 23. By using the synchronized clock signals of each sensor 21, 22, and 23 in this way, detection data from each sensor 21, 22, and 23 can be extracted in a common time series.

[0093] The relative relationship can be improved by using the flight status of aircraft 1 and the flight status of other aircraft 2 acquired during flight. However, depending on the situation, the relative relationship may be output without using predicted values ​​based on the flight status.

[0094] The estimation units 76 and 85 may use a state observer model in addition to a Kalman filter. The flight parameters data includes two types of detection data: detection data from the inertial sensor 21 and detection data from the satellite positioning sensor 22. However, depending on the situation, only one of the detection data may be used.

[0095] The surrounding airspace means the space around aircraft 1, and may include the air, as well as the ground and water. The object may be a moving or non-moving object located in the air, or a moving or non-moving object located on the ground or water.

[0096] The point cloud data only needs to be generated as data that can be extracted for each irradiation direction and irradiation time, showing the relative distance from aircraft 1 to the object, and the generated data structure is not limited.

[0097] The information output by the representative measurement point extraction unit 81 may be information based on the aircraft's gravity coordinate system. In this case, the representative measurement point extraction unit 81 may be configured to store or read conversion information for converting information from the sensor coordinate system to the aircraft 1's gravity coordinate system.

[0098] The fixed position of the LiDAR sensor on the aircraft only needs to be set in a position where it can detect objects, and the illustration is just one example. For example, multiple LiDAR sensors may be provided to detect objects. Specifically, LiDAR sensors may be provided to detect objects located above, below, in front of, behind, to the left of, or to the right of the aircraft.

[0099] In this embodiment, data with a short relative distance from the point cloud data was extracted as representative measurement points. However, it is sufficient to extract just one representative measurement point, and other extraction rules may be used. For example, the average value of multiple point cloud data may be used as representative measurement point data, or one region in the point cloud data with a high density of reflected data may be used as representative measurement point data. The value with a high intensity of reflected laser light may also be used as representative measurement point data.

[0100] As described above, the embodiments have been explained as examples of the technology disclosed in this application. However, the technology in this disclosure is not limited to the embodiments described above and can be applied to embodiments that have been modified, replaced, added, or omitted as appropriate. It is also possible to combine the components described in the embodiments to create new embodiments. For example, some components or methods in one embodiment may be applied to other embodiments, and some components in an embodiment can be separated from other components in that embodiment and extracted as appropriate. Among the components described in the attached drawings and detailed description are not only components that are essential for solving the problem, but also components that are not essential for solving the problem, in order to illustrate the technology.

[0101] The functions of the elements disclosed herein may be implemented using one or more circuits or processing circuits, including general-purpose processors, special-purpose processors, integrated circuits, ASICs (Application Specific Integrated Circuits), FPGAs (Field Programmable Gate Arrays), and / or conventional circuits. The functions of the elements disclosed herein may be implemented using one or more circuits or processing circuits, including a combination of general-purpose processors, special-purpose processors, integrated circuits, ASICs, FPGAs, and conventional circuits. One or more circuits or processing circuits may be programmed using one or more programs stored together or individually in one or more memories, or may be otherwise configured to perform the disclosed functions. A processor is considered a processing circuit or circuit because it includes transistors and other circuits. A processor may be a programmed processor that executes programs stored in memory. In this disclosure, a circuit, unit, or means is hardware that performs the enumerated functions individually or in combination with each other, or hardware programmed to perform the enumerated functions individually or in combination with each other. The hardware may be any hardware disclosed herein that is programmed or configured to perform the enumerated functions. The computer program, including computer instructions, is stored in memory. The computer instructions provide logic and routines that enable the hardware to perform the methods disclosed herein. The hardware includes, for example, processing circuits or circuits. The computer program may be implemented in a known format on computer-readable storage media, computer program products, memory devices, recording media such as CD-ROMs or DVDs, and / or in the memory of FPGAs or ASICs.

[0102] The embodiments described above are specific examples of the following embodiments. The aircraft flight navigation support method in the first embodiment acquires flight parameter data showing flight parameters including the absolute position and absolute attitude of the aircraft in flight, acquires point cloud data showing information related to the relative distance from the aircraft in flight to an object detected by a LiDAR sensor, calculates the relative relationship between the aircraft in flight and the object based on the flight parameter data and the point cloud data, and outputs relative relationship information showing the calculated relative relationship.

[0103] According to the first embodiment, relative relationship information indicating the relative relationship between the aircraft in flight and an object is output based on point cloud data from the LiDAR sensor and flight parameter data. This supports aircraft flight that takes into account objects in the airspace surrounding the aircraft. By using flight parameter data and point cloud data, relative relationships that take into account changes in the aircraft's state can be calculated. This improves the accuracy of calculating the relative relationship between the aircraft and the object. Since any object that can reflect the laser light emitted by the LiDAR sensor can be detected, the types of detectable objects can be increased.

[0104] The aircraft flight navigation support method in the second embodiment may be configured such that, in the flight navigation support method in the first embodiment, calculating the relative relationship includes calculating the relative relationship based on the flight parameters data associated with the synchronization information and the point cloud data associated with the synchronization information.

[0105] According to the second embodiment, point cloud data acquired at the same time as the flight parameters data is used to calculate the relative relationship between the aircraft and the object. This allows for accurate calculation of the relative relationship between the aircraft and the object. In particular, when the aircraft is moving at high speed, high-precision calculation of the relative relationship between the aircraft and the object is effective.

[0106] The third aspect of the aircraft flight navigation support method may be configured such that, in the first or second aspect of the flight navigation support method, the relative relationship includes the relative speed between the aircraft and the object, and the calculation of the relative relationship includes calculating the relative speed based on the time change of information indicated by a plurality of point cloud data acquired sequentially over time.

[0107] According to the third embodiment, the relative velocity between the aircraft and the object can be calculated from the time change of information shown in the point cloud data, making it easier to predict the movement of the object relative to the aircraft. This allows for appropriate support for flight that takes into account objects moving in the airspace surrounding the aircraft.

[0108] The fourth aspect of the aircraft flight navigation support method may be configured such that, in the flight navigation support method of any of the first to third aspects, calculating the relative relationship includes estimating the relative relationship based on the relative relationship between the aircraft and the object predicted based on the information indicated by the point cloud data acquired in the past, and the relative relationship between the aircraft and the object obtained based on the information indicated by the point cloud data acquired in the present.

[0109] According to the fourth embodiment, even when the point cloud data contains noise, or when the information contained in the point cloud data acquired sequentially over time is discrete, the accuracy of calculating the relative relationship between the aircraft and the object can be improved.

[0110] The fifth aspect of the aircraft flight navigation support method may be configured such that, in the fourth aspect of the flight navigation support method, the estimation of the relative relationship includes estimation using a Kalman filter.

[0111] According to the fifth aspect, the use of a Kalman filter allows for easy and highly accurate detection of the relative relationship between the aircraft and the object.

[0112] The aircraft flight navigation support method in the sixth embodiment may be configured such that, in the flight navigation support method in any of the first to fifth embodiments, calculating the relative relationship includes extracting point data representing the relative distance to the object from the point cloud data in accordance with predetermined rules, and calculating the relative relationship based on the extracted point data.

[0113] According to the sixth embodiment, by not using point data other than the point data representing the relative distance to the object in the calculation, the calculation can be simplified and the calculation of relative relationships can be expedited.

[0114] The seventh aspect of the aircraft flight navigation support method may be configured such that, in the flight navigation support method of any of the first to sixth aspects, actuators that change the flight behavior of the aircraft are controlled based on the relative relationship indicated by the output relative relationship information. According to the seventh aspect, aircraft flight control according to the relative relationship between the aircraft and the object can be realized.

[0115] The aircraft flight navigation support method in the eighth aspect may be configured such that, in the flight navigation support method in the seventh aspect, controlling the actuator includes controlling the actuator based on the relative relationship information so that the relative distance is maintained at or above a predetermined control interval. According to the eighth aspect, the unmanned aircraft can avoid collision with an object through autonomous flight.

[0116] The aircraft flight navigation support method in the ninth embodiment may be configured such that, in the flight navigation support method in the seventh embodiment, controlling the actuator includes controlling the actuator based on the relative relationship information so that the aircraft is guided toward the object. According to the ninth embodiment, it is possible to achieve navigation toward the object, navigation following the object, etc.

[0117] The aircraft flight navigation support program in the tenth embodiment causes a processor to execute the flight navigation support method in any of the first to ninth embodiments. The flight navigation support program may be, for example, a program recorded on a non-temporary, tangible computer-readable recording medium, and may be configured to be read from the recording medium using a drive device for the recording medium and installed on a computer. The flight navigation support program may be, for example, a program that can be distributed via a transmission medium such as the Internet, and may be configured to be downloaded and installed on a computer.

[0118] An aircraft flight navigation support system in an eleventh embodiment includes: a laser rangefinder that scans the space around an aircraft in flight with laser light and receives reflected light from an object in the space to detect the relative distance to the object and outputs data related to the relative distance; an actuator that changes the flight state of the aircraft; and a processing circuit that calculates the relative relationship between the aircraft in flight and the object based on the data and controls the actuator based on the calculated relative relationship.

[0119] According to the eleventh embodiment, relative relationship information indicating the relative relationship between the aircraft in flight and an object is output based on data from the laser ranging sensor. This supports flight that takes into account objects in the airspace surrounding the aircraft. Since any object that can reflect the laser light emitted by the laser ranging sensor can be detected, the types of detectable objects can be increased.

[0120] An aircraft flight navigation support system in a twelfth embodiment further includes, in an aircraft flight navigation support system in an eleventh embodiment, a flight parameter sensor for acquiring flight parameter data indicating flight parameters including the absolute position and absolute attitude of the aircraft in flight, and the processing circuit may be configured to calculate the relative relationship between the aircraft in flight and the object based on the flight parameter data and point cloud data indicating information related to the relative distance, corresponding to data related to the relative distance.

[0121] According to the twelfth embodiment, a relative relationship that takes into account changes in the aircraft's state can be calculated based on flight parameter data and point cloud data indicating information related to the relative distance from the aircraft to the object during flight. This improves the accuracy of calculating the relative relationship between the aircraft and the object.

[0122] An aircraft flight navigation support system in the 13th embodiment may be configured such that, in an aircraft flight navigation support system in the 11th or 12th embodiment, the aircraft is an unmanned aerial vehicle equipped with fixed wings and propellers.

[0123] According to the 13th embodiment, even aircraft that need to fly at high speed to obtain lift using fixed wings can perform flight control based on their relative relationship with an object with a relatively inexpensive configuration.

[0124] 1. Aircraft 1b. Main wing, fixed wing 1e. Propulsion propeller 2. Other aircraft, target object 10. Flight navigation support system 11. Propulsion source, actuator 12, 13, 14. Actuator 21. Inertial sensor, flight parameters sensor 22. Satellite positioning sensor, flight parameters sensor 23. LiDAR sensor (laser ranging sensor) 25. Flight control computer 111. Processor 114. Control program T. Target object, object

Claims

1. An aircraft flight navigation support method comprising: acquiring flight data showing the aircraft's position and attitude during flight; acquiring point cloud data showing information related to the relative distance from the aircraft to an object during flight, detected by a LiDAR sensor; calculating the relative relationship between the aircraft and the object during flight based on the flight data and the point cloud data; and outputting relative relationship information showing the calculated relative relationship.

2. The flight navigation support method according to claim 1, wherein calculating the relative relationship includes calculating the relative relationship based on the flight parameters data associated with the synchronization information and the point cloud data associated with the synchronization information.

3. The flight navigation support method according to claim 1, wherein the relative relationship includes the relative speed between the aircraft and the object, and calculating the relative relationship includes calculating the relative speed based on the time change of information indicated by a plurality of point cloud data acquired sequentially over time.

4. The flight navigation support method according to claim 1, wherein calculating the relative relationship includes estimating the relative relationship between the aircraft and the object based on the relative relationship between the aircraft and the object predicted based on the information indicated by the point cloud data acquired in the past, and the relative relationship between the aircraft and the object obtained based on the information indicated by the point cloud data acquired in the present.

5. The flight navigation support method according to claim 4, wherein the estimation of the relative relationship includes estimation using a Kalman filter.

6. The flight navigation support method according to claim 1, wherein calculating the relative relationship includes extracting point data representing the relative distance to the object from the point cloud data in accordance with predetermined rules, and calculating the relative relationship based on the extracted point data.

7. The flight navigation support method according to claim 1, wherein an actuator that changes the flight state of the aircraft is controlled based on the relative relationship indicated by the output relative relationship information.

8. The flight navigation support method according to claim 7, wherein controlling the actuator includes controlling the actuator based on the relative relationship information so that the relative distance is maintained at or above a predetermined control interval.

9. The flight navigation assistance method according to claim 7, wherein controlling the actuator includes controlling the actuator so that the aircraft is guided to the object based on the relative relationship information.

10. An aircraft flight navigation support program that causes a processor to execute the flight navigation support method according to any one of claims 1 to 9.

11. An aircraft flight navigation support system comprising: a laser rangefinder that scans the space around an aircraft in flight with laser light and detects the relative distance to an object by receiving reflected light from an object in the space and outputs data related to the relative distance; and a processing circuit that calculates the relative relationship between the aircraft in flight and the object based on the data and controls an actuator that changes the flight behavior of the aircraft based on the calculated relative relationship.

12. The flight navigation support system according to claim 11, further comprising a flight parameter sensor for acquiring flight parameter data indicating flight parameters including the absolute position and absolute attitude of the aircraft in flight, wherein the processing circuit calculates the relative relationship between the aircraft in flight and the object based on the flight parameter data and point cloud data indicating information relating to the relative distance, corresponding to data relating to the relative distance.

13. The flight navigation support system according to claim 11, which is equipped on an unmanned aerial vehicle having fixed wings and a propeller.

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