Flight body detection method, flight body detector, and flight body detection program

Abstract

To provide a flight body detection method, a flight body detector, and a flight body detection program that achieve miniaturization and weight reduction, and that detect a flight body without being affected by a visual field state.SOLUTION: A flight body detection method includes the steps of: collecting sound of the surroundings of a flight body during a flight to create sound data; analyzing modulation frequencies of the created sound data; and extracting only a modulation frequency at which a magnitude of amplitude modulation is equal to or larger than a prescribed threshold and which has an order component, as a peak of operation sound of another flight body, from the amplitude modulation for each of the modulation frequencies.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an aircraft detection method, an aircraft detection device, and an aircraft detection program. [Background technology]

[0002] In recent years, the use of drones and other unmanned aerial vehicles has been attracting attention due to factors such as a declining working population. Drones generally fly at low altitudes to avoid collisions with passenger aircraft, but commercial helicopters, including emergency medical helicopters, also fly at low altitudes for approximately half of their total flight time. This means that drones and commercial helicopters may fly in the same airspace, creating a risk of collision. Drones are difficult for helicopter pilots to see, and drones are more maneuverable, so drones must be able to detect flying objects such as helicopters and avoid collisions.

[0003] For example, Patent Document 1 discloses a system that uses position information of an aircraft to issue an alarm when the aircraft comes close to another aircraft. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2022-147583 Summary of the Invention [Problem to be solved by the invention]

[0005] Methods such as those described in Patent Document 1 may not function properly if the acquired position information contains errors for some reason. Furthermore, with methods of detecting flying objects using only a camera, it is difficult for the camera to accurately grasp the surrounding situation when flying in poor visibility conditions, such as at night or in bad weather. While methods of detecting flying objects using radar can detect the position of flying objects even in poor visibility conditions, the sensors become larger and heavier, and the accompanying battery size and weight increase, making them difficult to install on small drones and adversely affecting the drone's continuous flight time.

[0006] The object of the present disclosure is to provide an aircraft detection method, an aircraft detection device, and an aircraft detection program that are small and lightweight and capable of accurately detecting aircraft regardless of field of view conditions. [Means for solving the problem]

[0007] A method for detecting an aircraft according to an embodiment of the present invention includes: The first step is to collect sounds around the aircraft during flight and create sound data. a second step of analyzing the modulation frequency of the created sound data and calculating the magnitude of amplitude modulation for each modulation frequency; and a third step of extracting, from the magnitude of the amplitude modulation for each modulation frequency, only modulation frequencies whose magnitude of amplitude modulation is equal to or greater than a predetermined threshold and which have order components as peaks of the operation noise of the other flying object.

[0008] In addition, in the aircraft detection method according to one embodiment of the present invention, The third step is a first detection filter application step for extracting modulation frequencies whose amplitude modulation magnitude is equal to or greater than a predetermined threshold value from the amplitude modulation magnitude for each modulation frequency; a second detection filter application step of identifying a maximum modulation frequency having a maximum amplitude modulation magnitude among the extracted modulation frequencies, performing a range setting process to set a predetermined frequency range from the maximum modulation frequency, performing a deletion process to delete the modulation frequencies present in the predetermined frequency range except for the maximum modulation frequency, and then performing the range setting process and the deletion process after excluding the frequency range for which the range setting process has been completed up to that point, and repeating the range setting process and the deletion process until the range setting process and the deletion process are completed for the entire range of the sound data; and a third detection filter application step of extracting only modulation frequencies having order components from the modulation frequencies extracted in the second detection filter application step as peaks of the operation sounds of the other aircraft.

[0009] In addition, in the aircraft detection method according to one embodiment of the present invention, The first step is Acquiring sounds around the flying object using a plurality of microphones; The processing includes correcting the phases of the sound data acquired by the plurality of microphones so that they overlap.

[0010] In addition, in the aircraft detection method according to one embodiment of the present invention, The first step is The method further includes processing to emphasize the magnitude of amplitude modulation of the sound data.

[0011] In addition, in the aircraft detection method according to one embodiment of the present invention, In the third step, when a peak of the operation sound of the other flying object is detected continuously for a predetermined period of time, it is determined that the operation sound of the other flying object has been detected.

[0012] In addition, in the aircraft detection method according to one embodiment of the present invention, The first step is Acquiring sounds around the flying object using a plurality of microphone arrays; The method further includes a process of estimating the direction in which the other flying object is located by identifying the sound data acquired by each of the multiple microphone arrays that has the largest amplitude modulation of the other flying object.

[0013] Moreover, an aircraft detection device according to an embodiment of the present invention includes: an input unit for acquiring sounds around the flying object; a control unit that detects other flying objects based on the sound acquired by the input unit, The control unit a first step of collecting sounds around the flying object and creating sound data; a second step of analyzing the modulation frequency of the created sound data and calculating the magnitude of amplitude modulation for each modulation frequency; and a third step of extracting, from the magnitude of the amplitude modulation for each modulation frequency, only modulation frequencies whose magnitude of amplitude modulation is equal to or greater than a predetermined threshold and which have order components as peaks of the operation noise of the other flying object.

[0014] Furthermore, an aircraft detection program according to an embodiment of the present invention includes: On the computer, The first step is to collect sounds around the aircraft during flight and create sound data. a second step of analyzing the modulation frequency of the created sound data and calculating the magnitude of amplitude modulation for each modulation frequency; and a third step of extracting, from the magnitude of the amplitude modulation for each modulation frequency, only modulation frequencies whose magnitude of amplitude modulation is equal to or greater than a predetermined threshold and which have order components as peaks of the operation noise of the other flying object. [Effects of the Invention]

[0015] The flying object detection method, flying object detection device, and flying object detection program disclosed herein are small and lightweight, and can accurately detect flying objects regardless of field of view conditions. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a schematic diagram showing an example of a usage mode of an aircraft detection device according to an embodiment of the present disclosure. FIG. [Figure 2] 1 is a block diagram illustrating a configuration of an aircraft detection device according to an embodiment of the present disclosure. [Figure 3] FIG. 2 is a diagram illustrating an example of a configuration of an input unit according to an embodiment of the present disclosure. [Figure 4] FIG. 1 is an image diagram of a method for acquiring frames of sound data according to an embodiment of the present disclosure. [Figure 5A] FIG. 10 is an image diagram of sound data after modulation frequency analysis according to an embodiment of the present disclosure. [Figure 5B] FIG. 10 is an image diagram of sound data after a first detection filter has been applied according to an embodiment of the present disclosure. [Figure 6A] FIG. 10 is an image diagram of sound data during a second detection filter application process according to an embodiment of the present disclosure. [Figure 6B] FIG. 10 is an image diagram of sound data after a second detection filter has been applied according to an embodiment of the present disclosure. [Figure 7A] FIG. 10 is an image diagram of sound data during a third detection filter application process according to an embodiment of the present disclosure. [Figure 7B] FIG. 10 is an image diagram of sound data after application of a third detection filter according to an embodiment of the present disclosure. [Figure 8] 10 is a flowchart illustrating an example of the operation of an aircraft detection device according to an embodiment of the present disclosure. [Figure 9] 10 is a flowchart illustrating an example of the operation of an aircraft detection device according to an embodiment of the present disclosure. [Figure 10A] FIG. 2 is a diagram illustrating a first example of sound data before application of a detection filter according to an embodiment of the present disclosure. [Figure 10B] FIG. 2 is a diagram illustrating a first example of sound data after a detection filter is applied according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0017] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0018] Fig. 1 is a schematic diagram showing an example of a usage mode of an aircraft detection device according to an embodiment of the present disclosure. Fig. 2 is a block diagram showing the configuration of an aircraft detection device 1 according to an embodiment of the present disclosure.

[0019] The aircraft detection device 1 is a device mounted on an aircraft 2, such as an unmanned aerial vehicle (UAV) including a drone. The aircraft detection device 1 uses acoustics to detect an aircraft 3 other than the aircraft on which the aircraft detection device 1 is mounted. The other aircraft 3 is, for example, a helicopter.

[0020] The aircraft detection device 1 includes a control unit 11, a storage unit 12, and an input unit 13.

[0021] The control unit 11 executes various processes related to the operation of the flying object detection device 1 and controls each unit of the flying object detection device 1. The control unit 11 includes at least one processor, at least one dedicated circuit, or a combination of these. The processor is a general-purpose processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), or a dedicated processor specialized for a specific process. The control unit 11 may realize its control functions by executing a program stored in the memory unit 12.

[0022] The storage unit 12 includes at least one semiconductor memory, at least one magnetic memory, at least one optical memory, or a combination thereof. The storage unit 12 functions as, for example, a main storage device, an auxiliary storage device, or a cache memory. The storage unit 12 stores, for example, programs and data used in the operation of the flying object detection device 1, and data obtained by the operation of the flying object detection device 1.

[0023] The input unit 13 includes a microphone array having two or more microphones. The microphones are, for example, condenser microphones. The microphone array may have a structure in which two or more microphones are arranged at equal intervals in a straight line, as shown in FIG. 3. The input unit 13 collects sounds around the aircraft 2 and creates sound data. The input unit 13 outputs the created sound data to the control unit 11.

[0024] Next, a description will be given of the operation of the flying object detection device 1. In this embodiment, a case will be described in which the input unit 13 is a microphone array in which five microphones are arranged in a straight line at equal intervals of 5 cm.

[0025] (How to set the threshold) The input unit 13 collects the operating sound of the aircraft 2 equipped with the aircraft detection device 1. The operating sound is collected by moving the aircraft 2 on one of the straight lines on which the microphones are arranged. The sound is collected in a situation where no other aircraft 3 is present. Here, the direction in which the aircraft 2 is located is defined as 180°, and the opposite direction in which other aircraft 3 are assumed to be present is defined as 0°. The control unit 11 acquires sound data of the operating sound of the aircraft 2 collected in a situation in which no other aircraft 3 is present as data for multiple frames. The control unit 11 may calculate and average the spectral correlation density of each frame to calculate the distribution of the magnitude of amplitude modulation for each modulation frequency.

[0026] The control unit 11 sets a threshold value for determining the presence of other flying objects 3 based on the calculated distribution of the amplitude modulation magnitude for each modulation frequency. The threshold value is set by using, for example, the Hotelling T 2 The law may be used.

[0027] (Method of emphasizing the operation sounds of other flying objects 3) The input unit 13 collects sounds around the flying object 2. The control unit 11 processes sound data based on the sounds collected by the input unit 13 for each frame. For example, as shown in FIG. 4, the control unit 11 may process frames that are shifted by one second, with one frame being five seconds. In this case, the overlap rate is 80%. In other words, the control unit 11 may process frames that overlap with the previous and next frames within a range of 80% for each second.

[0028] The control unit 11 applies a fixed delay-sum beamformer to sound signals collected from the 0° direction, which is the direction in which other flying objects 3 are assumed to be located. That is, the control unit 11 calculates the delay time that occurs in the input to each microphone when collecting sound from the 0° direction, based on the spacing between microphones in the microphone array and the speed of sound. Based on the calculated delay time, the control unit 11 sets delay elements so that the phases of the 0° direction sound data input to each microphone overlap, and performs phase correction.

[0029] By performing phase correction, the sound in the 0° direction, i.e., the sound of the other flying object 3, is emphasized because the phase is aligned. On the other hand, the sound in the 180° direction, i.e., the sound of the flying object 2, is suppressed because the phase is not aligned. This allows the control unit 11 to particularly emphasize the sound data in the 0° direction.

[0030] Note that applying a fixed delay and sum beamformer to sound data collected by a microphone array can enhance not only sounds in the 0° direction, but also sounds 30° in front and behind that direction. In other words, applying a fixed delay and sum beamformer can enhance sounds in the range of -30° to 30° relative to the microphone array. That is, in this invention, it is possible to enhance the sounds of other flying objects 3 present in directions between -30° and 30° per microphone array.

[0031] (Amplitude modulation enhancement method for sound data) The control unit 11 emphasizes the amplitude modulation of the sound data based on the sound collected by the input unit 13. Since the amplitude modulation is information necessary for detecting the operation sounds of other aircraft 3, emphasizing the amplitude modulation can prevent the operation sounds of other aircraft 3 from being missed when detected. If a signal with amplitude modulation is x, the signal x' with emphasized amplitude modulation can be calculated using equation (1).

number

[0032] (Method of analyzing modulation frequency) The control unit 11 analyzes the modulation frequency of the sound data based on the sound collected by the input unit 13 and calculates the magnitude of the amplitude modulation at each modulation frequency. Below, a method of analyzing the modulation frequency by calculating the spectral correlation density will be described, but the analysis method is not limited to this.

[0033] Hereinafter, a method in which the control unit 11 calculates the magnitude of the amplitude modulation at each modulation frequency by calculating the spectral correlation density will be described. The spectral correlation density S for the modulation frequency a and the frequency f is x is calculated by double Fourier transform of the autocorrelation function. The control unit 11 performs Fourier transform on the autocorrelation coefficient with respect to time t according to the following formula (2). In the following formula (2), x * denotes the complex conjugate of the signal.

number

[0034] Next, the control unit 11 further performs a Fourier transform on the cyclic autocorrelation coefficients Rx(a, τ) calculated by the Fourier transform of the autocorrelation coefficients, with respect to τ, according to the following equation (3).

number

[0035] The spectral correlation density Sx(a,f) calculated by double Fourier transform of the autocorrelation coefficient does not take into account the passage of time, so as shown in the following formula (4), Sx calculated by dividing the signal x into short periods is averaged in the frequency f direction and converted into a function of modulation frequency a and time t. In the following formula (4), X is the signal vector, N is the overlap size, W is the window size, and f max indicates the maximum frequency.

number

[0036] (How to apply other aircraft operation sound detection filters) The control unit 11 applies an other aircraft operation sound detection filter to the sound data that has detected the magnitude of the amplitude modulation at each modulation frequency through an analysis of the modulation frequency. This makes it possible to detect amplitude modulation specific to other aircraft 3. The other aircraft operation sound detection filter is composed of three filters, a first detection filter to a third detection filter. The first detection filter to the third detection filter will be described below. First, a method for applying the first detection filter will be described using Figures 5A and 5B.

[0037] FIG. 5A is a diagram showing an example of sound data in which the magnitude of amplitude modulation at each modulation frequency has been detected by analyzing the modulation frequency. FIG. 5B is a diagram showing an example of sound data in which a first detection filter has been applied to FIG. 5A. In applying the first detection filter, the control unit 11 extracts only modulation frequencies whose magnitude of amplitude modulation exceeds a predetermined threshold from the sound data in which the magnitude of amplitude modulation at each modulation frequency has been detected by analyzing the modulation frequency. Since the threshold is set based on the amplitude modulation of the operating sound of the aircraft 2, applying the first detection filter makes it possible to extract only modulation frequencies that may be the operating sound of other aircraft 3.

[0038] Next, a method for applying the second detection filter will be described with reference to FIGS. 6A and 6B. FIG. 6A is a diagram illustrating the application of the second detection filter to sound data to which the first detection filter has been applied. FIG. 6B is a diagram illustrating an example of sound data to which the second detection filter has been applied. In applying the second detection filter, the control unit 11 identifies a first maximum modulation frequency, which is the modulation frequency with the largest amplitude modulation within the entire range of sound data to which the first detection filter has been applied. Next, the control unit 11 sets a first frequency range, which is a predetermined frequency range around the first maximum modulation frequency. In FIG. 6A, the predetermined frequency range is set to 25 Hz around the first maximum modulation frequency, but is not limited to this. The predetermined frequency range may be determined, for example, from the propeller rotation speed range of other anticipated aircraft 3. Then, the control unit 11 performs a deletion process to delete data of modulation frequencies other than the first maximum modulation frequency from among the modulation frequencies present within the first frequency range.

[0039] After setting the first frequency range, the control unit 11 identifies a second maximum modulation frequency, which is the modulation frequency with the largest amplitude modulation, after excluding the first frequency range. The control unit 11 then sets a second frequency range, which is a predetermined frequency range around the second maximum modulation frequency. The control unit 11 then performs a deletion process in the second frequency range. Thereafter, the control unit 11 repeats the same process of identifying the maximum modulation frequency, setting the frequency range, and deleting the modulation frequency range, excluding the modulation frequency ranges that have been set so far, until a modulation frequency range is set in the entire range of the sound data to which the first detection filter has been applied.

[0040] The following description will be given using Figure 6A as a specific example. In the following description, the maximum modulation frequency extracted nth by the second detection filter among the modulation frequencies extracted by the first detection filter will be referred to as the nth maximum modulation frequency, and the frequency range set corresponding to this maximum modulation frequency will be referred to as the nth frequency range. In the following description, the modulation frequency of f1 will be 11 Hz, the modulation frequency of f2 will be 90 Hz, the modulation frequency of f3 will be 67 Hz, and the modulation frequency of f4 will be 45 Hz.

[0041] The control unit 11 identifies the modulation frequency f1, which has the largest amplitude modulation magnitude, as the first maximum modulation frequency among the sound data with a modulation frequency of 10 to 100 Hz to which the first detection filter is applied. Next, the control unit 11 sets a first frequency range of 25 Hz around f1. Thereafter, the control unit 11 deletes data of modulation frequencies other than f1 from among the modulation frequencies within the first frequency range.

[0042] Next, the control unit 11 specifies the modulation frequency f2 with the largest amplitude modulation outside the first frequency range as the second maximum modulation frequency. The control unit 11 then sets a second frequency range of 25 Hz around f2. The control unit 11 then deletes data on the modulation frequencies of the amplitude modulation in the second frequency range other than f2.

[0043] Next, the control unit 11 identifies the modulation frequency f3, which has the largest amplitude modulation outside the first and second frequency ranges, as the third maximum modulation frequency. The control unit 11 then sets a third frequency range, which is 25 Hz around f3. The control unit 11 then deletes data on modulation frequencies other than f3 from among the modulation frequencies in the third frequency range.

[0044] Next, the control unit 11 identifies the modulation frequency f4, which has the largest amplitude modulation outside the first to third frequency ranges, as the fourth maximum modulation frequency. Subsequently, the control unit 11 sets 25 Hz around f4 as the fourth frequency range. Thereafter, the control unit 11 deletes data of modulation frequencies other than f4 from among the modulation frequencies within the fourth frequency range. By setting the fourth frequency range, the frequency range has been set over the entire range of sound data to which the first detection filter has been applied, so the control unit 11 ends application of the second detection filter.

[0045] Next, a method for applying the third detection filter will be described with reference to Figures 7A and 7B. Figure 7A is a diagram showing an image of how it is determined whether the modulation frequencies extracted by the second detection filter have order components (whether they are equally spaced). Figure 7B is a diagram showing an example of sound data to which the third detection filter has been applied. In applying the third detection filter, the control unit 11 multiplies the lowest modulation frequency extracted by the second detection filter by 1, the second lowest modulation frequency by 2, and the third lowest modulation frequency by 3. In this way, the control unit 11 multiplies the n-th lowest modulation frequency by 1 / n, in order from the lowest modulation frequency.

[0046] Next, the control unit 11 calculates the difference between the modulation frequencies after fractional multiplication between the lowest modulation frequency before the fractional multiplication process and the modulation frequencies before and after the lowest modulation frequency that are closest in value to the modulation frequency before and after the fractional multiplication process. If either of the calculated differences is within a predetermined range, the control unit 11 considers the lowest modulation frequency to have order components (equally spaced) and extracts it as the operation sound of another aircraft 3. The predetermined range is, for example, less than ±0.5 Hz, but is not limited to this. The control unit 11 repeats the same processing and judgment for the lowest modulation frequency, excluding the modulation frequency for which judgment has been completed, until the above processing and judgment are completed for the entire range of modulation frequencies of the sound data to which the second detection filter has been applied.

[0047] The following description will be given using FIG. 7A as a specific example. Here, the predetermined range is less than ±0.5 Hz. The control unit 11 performs fractional multiplication on f1, the lowest modulation frequency in the sound data. Because f1 is the lowest modulation frequency in the sound data, it is multiplied by 1 (1 / 1). Because f1 is 11 Hz, the value after fractional multiplication of f1 is 11 Hz. Next, the control unit 11 performs fractional multiplication on f4, the second lowest modulation frequency in the sound data. Because f4 is the second lowest modulation frequency in the sound data, it is multiplied by 1 / 2. Because f4 is 45 Hz, the value after fractional multiplication of f4 is 22.5 Hz. Here, the control unit 11 compares the values ​​after fractional multiplication of f1 and f4. The value of f1 is 11 Hz, while the value of f4 is 22.5 Hz. The difference is 11.5 Hz, which is outside the predetermined range. Therefore, f1 does not have any order components in relation to f4. Since f1 is the lowest modulation frequency, if it does not have any order components in relation to f4, then f1 can be said to be a modulation frequency that does not have any order components. Therefore, f1 is a modulation frequency that does not have any order components.

[0048] Next, the control unit 11 performs fractional multiplication on f3, the third lowest modulation frequency in the sound data. Since f3 is the third lowest modulation frequency in the sound data, it is multiplied by 1 / 3. Since f3 is 68 Hz, the value of f3 after fractional multiplication is approximately 22.7 Hz. Here, the control unit 11 compares the values ​​of f4 and f3 after fractional multiplication. The value of f4 is 22.5 Hz, while the value of f3 is approximately 22.7 Hz. The difference is 0.2 Hz, which is within the specified range. Therefore, f4 and f3 have order components.

[0049] Next, the control unit 11 performs fractional multiplication on f2, the fourth lowest modulation frequency in the sound data. Because f2 is the fourth lowest modulation frequency in the sound data, it is multiplied by 1 / 4. Because f2 is 90 Hz, the value of f2 after fractional multiplication is 22.5 Hz. Here, the control unit 11 compares the values ​​of f4 and f3 after fractional multiplication. The value of f3 is approximately 22.7 Hz, while the value of f2 is 22.5 Hz. The difference is 0.2 Hz, which is within the specified range. Therefore, f2 has order components.

[0050] With the processing of f2, processing is completed for the entire range of sound data to which the second detection filter has been applied, and therefore application of the third detection filter is terminated.

[0051] An example of control processing of the flying object detection device 1 according to this embodiment having the above configuration will be described below with reference to Fig. 8 and Fig. 9. Fig. 8 is a flowchart illustrating the first processing. Fig. 9 is a flowchart illustrating the second processing.

[0052] In this embodiment, the flying object detection device 1 performs a first process of setting a threshold value for determining the presence of other flying objects 3 before or when the device is mounted on the flying object 2. Thereafter, while the flying object 2 is flying, a second process of determining whether other flying objects 3 are present from sound data based on collected sounds is performed. The first process will be described below with reference to FIG. 8.

[0053] The control unit 11 acquires sound data based on the operation sound of the flying object 2, which has been created and output by the input unit 13, as data for multiple frames (step S101). The frames may be of any length and number. For example, the control unit 11 may acquire data for 10 frames, with one frame being one second. Furthermore, the frames may partially overlap each other.

[0054] Next, the control unit 11 calculates the spectral correlation density of each acquired frame (step S102). Thereafter, the control unit 11 averages each of the spectral correlation densities calculated in step S102 to obtain a distribution of amplitude modulation for each modulation frequency (step S103). After obtaining the distribution of amplitude modulation for each modulation frequency, the control unit 11 sets a threshold for determining the presence of other aircraft 3 based on the distribution and stores it in the memory unit 12 (step S104).

[0055] Next, the second process will be described with reference to FIG. 9. When the input unit 13 creates sound data based on sounds around the aircraft 2, the control unit 11 acquires the sound data as data for multiple frames (step S201). The frames may be of any length and number. Furthermore, the frames may partially overlap. For example, the control unit 11 may process frames that are shifted by one second, with one frame being five seconds. In this case, the overlap rate is 80%. In other words, the control unit 11 may process frames that overlap with the previous and next frames within a range of 80% every second.

[0056] The control unit 11 applies a fixed delay and sum beamformer to the input sound data and performs correction so that the phases of the sound data input to the input unit 13 from the 0° direction (the direction of the operation sound of the other aircraft 3) overlap (step S202).

[0057] The control unit 11 performs processing to emphasize the amplitude modulation of the sound data corrected in step S202 (step S203).

[0058] The control unit 11 performs modulation frequency analysis on the sound data whose amplitude modulation has been emphasized in step S203 (step S204).

[0059] The control unit 11 applies a filter for detecting the operation sounds of other aircraft to the sound data that has been subjected to the modulation frequency analysis in step S204, and extracts the operation sounds of other aircraft 3 (step S205).

[0060] The control unit 11 refers to the sound data to which the operation sound detection filter was applied in step S205 and determines whether there is a magnitude of amplitude modulation corresponding to the operation sound of another aircraft 3 (step S206). If such a peak is present (step S206: Yes), the control unit 11 determines whether the peak is detected continuously for a predetermined time (step S207). If the peak is detected continuously for a predetermined time (step S207: Yes), the control unit 11 determines that there is another aircraft 3 around the aircraft 2 (step S208). If there is no magnitude of amplitude modulation corresponding to the operation sound of another aircraft 3 or if it is not detected continuously for a predetermined time (step S206: No or step S207: No), the control unit 11 determines that there is no other aircraft 3 around the aircraft 2 (step S209).

[0061] (First Example) A first example of the flying object detection method of the flying object detection device 1 according to this embodiment will be described with reference to FIGS. 10A and 10B.

[0062] Fig. 10A is a diagram showing an example of processing up to step S204. Fig. 10B is a diagram showing an example of processing up to step S205 for the same sound data as Fig. 10A. In both cases, the darker the color, the greater the amplitude modulation.

[0063] The detection process for the flying object shown in Figures 10A and 10B was carried out using the following procedure. First, the operating noise of a drone corresponding to flying object 2 was measured in an anechoic chamber. The measurement was carried out using a microphone array in which five microphones were arranged in a straight line at intervals of 5 cm. The drone was operated at a position 30 cm away from the 0° direction of the microphone array, and measurements were carried out.

[0064] Next, measurements were made of the operating noise and environmental noise of a helicopter, equivalent to another flying object 3. Measurements were taken outdoors, with helicopters coming within a 5km radius of the measurement point. Measurements lasted approximately 2 minutes per helicopter approach. The measurement method employed was that an operator waiting at a different location from the measurement point would notify the person making the measurement of the approaching helicopter, and the measurement would end when the helicopter passed the measurement point. Using the above method, the operating noise of a helicopter was measured when the separation distance was between 0.5 and 5km.

[0065] Thereafter, the first and second processes according to the present invention were applied to the measured drone operation sounds, helicopter operation sounds, and environmental sounds.

[0066] 10A, when the helicopter arrived at a point about 600 m from the measurement point, a large amplitude modulation was observed. In other words, by using sound data to which the other aircraft operation sound detection filter of the present invention (step S205) is not applied, another aircraft 3 located about 600 m in the direction of travel of aircraft 2 can be detected.

[0067] Referring to Figure 10B, when the helicopter arrived at a point approximately 2,500 m from the measurement point, a large amplitude modulation was observed. In other words, by adopting the aircraft detection method according to the present invention, it is possible to detect the operation sound of another aircraft 3 located approximately 2,500 m in the direction of travel of the aircraft 2. In other words, by applying the other aircraft operation sound detection filter (step S205) according to the present invention, the detectable distance of the other aircraft 3 is increased by more than four times. This allows the aircraft 2 to avoid the other aircraft 3 more safely and reliably.

[0068] As described above, by employing the air vehicle detection method according to the present disclosure, it is possible to detect other air vehicles 3 at long distances from sound data. In the air vehicle detection method according to the present disclosure, the only sensor used is a microphone array including multiple microphones, so it is possible to build a drone with a collision avoidance method that is small and lightweight, and is not affected by field of view conditions.

[0069] (Second Example) A second example of the flying object detection method of the flying object detection device 1 according to this embodiment will be described. In the second example, six microphone arrays were installed on the drone at 60° intervals. Measurements were otherwise performed under the same conditions as in the first example. Here, the front direction of the drone is defined as 0°, and the microphone array installed at the 0° direction is defined as the first array, the microphone array installed at the 60° direction is defined as the second array, the microphone array installed at the 120° direction is defined as the third array, the microphone array installed at the 180° direction is defined as the fourth array, the microphone array installed at the 240° direction is defined as the fifth array, and the microphone array installed at the 300° direction is defined as the sixth array.

[0070] When a fixed delay and sum beamformer was applied to sound data collected by six microphone arrays, the sound of a helicopter's operation was detected as being emphasized in the sound data collected by all microphone arrays, and the largest amplitude modulation was detected in the sound data collected by the third array. When a fixed delay and sum beamformer was applied to the sound data collected by the third array, sounds within a 90° to 150° range were emphasized, allowing the helicopter to be estimated to be located in a direction within that range. In other words, by applying the second embodiment of the present invention, it is possible to estimate the direction in which another aircraft 3 is located from the perspective of the aircraft 2. This allows the aircraft 2 to avoid the other aircraft 3 more safely and reliably.

[0071] The present disclosure is not limited to the above-described embodiments. For example, multiple blocks shown in the block diagrams may be integrated, or a single block may be divided. Instead of executing multiple steps shown in the flowcharts in chronological order as described, steps may be executed in parallel or in a different order depending on the processing capabilities of the device executing each step, or as needed. Other modifications are possible within the scope of the present disclosure.

[0072] For example, in the above-described embodiment, the control unit 11 and / or the storage unit 12 of the flying object detection device 1 may be a general-purpose computer such as a WS (Work Station) or PC (Personal Computer) installed in a facility such as a data center, rather than being mounted on the flying object 2. In this case, the control unit 11 and / or the storage unit 12 may be connected to the flying object detection device 1 via a network. [Explanation of symbols]

[0073] 1 Aircraft detection device 11 Control section 12 Storage section 13 Input section 2. Aircraft 3 Other flying objects

Claims

1. A method for detecting an aircraft in flight, in which an aircraft detects another aircraft, comprising: a first step of collecting sounds around the flying object and creating sound data; a second step of analyzing the modulation frequencies of the created sound data and calculating the magnitude of amplitude modulation for each modulation frequency; and a third step of extracting, from the magnitude of the amplitude modulation for each modulation frequency, only modulation frequencies whose magnitude of amplitude modulation is equal to or greater than a predetermined threshold and which have order components as peaks of the operation sounds of the other aircraft.

2. The third step is a first detection filter application step for extracting modulation frequencies whose amplitude modulation magnitude is equal to or greater than a predetermined threshold value from the amplitude modulation magnitude for each modulation frequency; a second detection filter application step of identifying a maximum modulation frequency having a maximum amplitude modulation magnitude among the extracted modulation frequencies, performing a range setting process to set a predetermined frequency range from the maximum modulation frequency, performing a deletion process to delete the modulation frequencies present in the predetermined frequency range except for the maximum modulation frequency, and then performing the range setting process and the deletion process after excluding the frequency range for which the range setting process has been completed up to that point, and repeating the range setting process and the deletion process until the range setting process and the deletion process are completed for the entire range of the sound data; and a third detection filter application step of extracting only modulation frequencies having order components from the modulation frequencies extracted in the second detection filter application step as peaks of the operation sounds of the other aircraft.

3. The first step comprises: Acquiring sounds around the flying object using a plurality of microphones; a process of correcting the phases of the sound data acquired by the plurality of microphones so that the phases overlap, The method for detecting an aircraft according to claim 1.

4. The first step comprises: further comprising processing for emphasizing the magnitude of amplitude modulation of the sound data. The method for detecting an aircraft according to claim 3.

5. In the third step, when a peak of the operation sound of the other aircraft is detected continuously for a predetermined period, it is determined that the operation sound of the other aircraft has been detected. The method for detecting an aircraft according to claim 1.

6. The first step comprises: Acquiring sounds around the flying object using a plurality of microphone arrays; The method further includes a process of estimating a direction in which the other flying object exists by identifying the sound data having the largest amplitude modulation of the other flying object among the sound data acquired by the plurality of microphone arrays. The method for detecting an aircraft according to claim 3.

7. An aircraft detection device, an input unit for acquiring sounds around the flying object; a control unit that detects other flying objects based on the sound acquired by the input unit, The control unit a first step of collecting sounds around the flying object and creating sound data; a second step of analyzing the modulation frequencies of the created sound data and calculating the magnitude of amplitude modulation for each modulation frequency; and a third step of extracting, from the magnitude of the amplitude modulation for each modulation frequency, only modulation frequencies whose magnitude of amplitude modulation is equal to or greater than a predetermined threshold and which have order components as peaks of the operation sounds of the other aircraft.

8. On the computer, A first step of collecting sounds around the flying object and creating sound data; a second step of analyzing the modulation frequencies of the created sound data and calculating the magnitude of amplitude modulation for each modulation frequency; and a third step of extracting, from the magnitude of the amplitude modulation for each modulation frequency, only modulation frequencies whose magnitude of amplitude modulation is equal to or greater than a predetermined threshold and which have order components as peaks of the operation sounds of other aircraft.

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