WO2013073399A1 - Dispositif et procédé de détection de la position d'un objet en mouvement - Google Patents

Dispositif et procédé de détection de la position d'un objet en mouvement Download PDF

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Publication number
WO2013073399A1
WO2013073399A1 PCT/JP2012/078623 JP2012078623W WO2013073399A1 WO 2013073399 A1 WO2013073399 A1 WO 2013073399A1 JP 2012078623 W JP2012078623 W JP 2012078623W WO 2013073399 A1 WO2013073399 A1 WO 2013073399A1
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Prior art keywords
moving body
parameter
sound
sound wave
sound pressure
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PCT/JP2012/078623
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English (en)
Japanese (ja)
Inventor
充伸 神沼
小野　順貴
安藤　繁
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日産自動車株式会社
国立大学法人東京大学
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Priority to JP2013544215A priority Critical patent/JP5757595B2/ja
Publication of WO2013073399A1 publication Critical patent/WO2013073399A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/80—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves
    • G01S3/802—Systems for determining direction or deviation from predetermined direction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/80—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves
    • G01S3/86—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves with means for eliminating undesired waves, e.g. disturbing noises
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes

Definitions

  • the present invention relates to an other moving body position detecting device and an other moving body position detecting method for detecting the position of another moving body with respect to the own moving body by reducing the influence of noise.
  • a method called the spatio-temporal gradient method has been proposed as a method for detecting the direction of a wave source from the wavefront at the observation point using a mathematical expression expressing the wavefront at the observation point for a wave coming from one wave source.
  • the spatiotemporal gradient method when a sound wave radiated from a point sound source is observed, the sound pressure (amplitude) of the observation point at any time, the temporal differentiation of the sound pressure, and the spatial differentiation of the sound pressure are used to The direction to the wave source and the distance between the observation point and the wave source are calculated.
  • Sound waves are weak to the influence of disturbance, and when there is a disturbance, it is difficult to calculate much of the position information of a desired wave source included in an arbitrary time frequency section.
  • disturbances include additive noise typified by waves generated by a moving body equipped with a device for detecting the direction of the wave source and waves reflected by other objects.
  • the position detection result of the wave source in a frequency band including noise is not localized in a desired direction, and the detection accuracy of the direction of the wave source is lowered.
  • an object of the present invention is to provide an other moving body position detecting device and an other moving body position detecting method capable of detecting the position of another moving body with respect to the own moving body by reducing the influence of noise. .
  • a mobile body position detection device is another mobile body position detection device mounted on a mobile body, and includes a traveling state detection unit, a sound wave input unit, a steady state determination unit,
  • the gist is to include a distributed processing unit, a target parameter calculation unit, and a direction detection unit.
  • the traveling state detection unit detects the traveling state of the mobile body.
  • the sound wave input unit inputs a sound wave including stationary noise and other moving body generated sound generated by the traveling of another moving body existing around.
  • the steady state determination unit determines whether or not the sound wave input by the sound wave input unit is in a steady state.
  • the covariance processing unit uses the sound pressure of the sound wave, the temporal differentiation of the sound pressure, and the element of the covariance matrix based on the spatial differentiation of the sound pressure as the first parameter for the sound wave that the steady state determination unit has determined to be not in the steady state. Is calculated as the second parameter for the sound wave determined to be in the steady state.
  • the target parameter calculation unit subtracts the second parameter corresponding to the traveling state detected by the traveling state detection unit from the first parameter, so that the sound pressure of the other moving body generated sound, the time differentiation of the sound pressure, the space of the sound pressure
  • the element of the covariance matrix based on the differentiation is calculated as the third parameter.
  • the direction detection unit detects the direction of the other moving body relative to the own moving body from the third parameter.
  • the other moving body position detecting method is an other moving body position detecting method for detecting the position of the other moving body with respect to the own moving body, and detects the traveling state of the own moving body. , Inputting sound waves including stationary noise and other moving body generated sound generated by the traveling of the other moving objects existing in the surroundings, determining whether or not the input sound waves are in a steady state, The elements of the covariance matrix based on the sound pressure, the temporal differentiation of the sound pressure, and the spatial differentiation of the sound pressure are the first parameter for the sound wave determined not to be in the steady state and the second parameter for the sound wave determined to be in the steady state.
  • the element of the third parameter Calculated as data, and summarized in that to detect the direction with respect to the own mobile body of said other mobile from said third parameter.
  • FIG. 1 is a block diagram illustrating a basic configuration of another mobile body position detection apparatus according to the first embodiment of the present invention.
  • FIG. 2 is a block diagram for explaining a sound wave input unit provided in the other moving body position detection apparatus according to the first embodiment of the present invention.
  • FIG. 3 is a schematic diagram for explaining how the other moving body position detection device according to the first embodiment of the present invention inputs sound waves.
  • FIG. 4 is a flowchart for explaining the other moving body position detection method according to the first embodiment of the present invention.
  • FIG. 5 is an example illustrating the processing steps of the other moving body position detection apparatus according to the first embodiment of the present invention.
  • FIG. 6 shows the result of detecting the direction of the other moving body by the spatiotemporal gradient method when the frequency is 2 kHz.
  • FIG. 1 is a block diagram illustrating a basic configuration of another mobile body position detection apparatus according to the first embodiment of the present invention.
  • FIG. 2 is a block diagram for explaining a sound wave input unit provided in the other moving
  • FIG. 7 shows the result of detecting the direction of the other moving body by the spatiotemporal gradient method when the frequency is 3 kHz.
  • FIG. 8 shows the result of detecting the direction of the other moving body by the spatiotemporal gradient method when the frequency is 4 kHz.
  • FIG. 9 shows the result of detecting the direction of the other moving body by the spatiotemporal gradient method when the frequency is 5 kHz.
  • FIG. 10 shows the result of detecting the direction of the other moving body by the spatiotemporal gradient method when the frequency is 6 kHz.
  • FIG. 11 shows the result of detecting the direction of the other moving body by the spatiotemporal gradient method when the frequency is 7 kHz.
  • FIG. 12 shows a target direction detection result when the other moving body position detection method according to the first embodiment of the present invention is applied in the case of a frequency of 2 kHz.
  • FIG. 13 shows a target direction detection result when the other moving body position detection method according to the first embodiment of the present invention is applied to a frequency of 3 kHz.
  • FIG. 14 shows a target direction detection result when the other moving body position detection method according to the first embodiment of the present invention is applied to a frequency of 4 kHz.
  • FIG. 15 shows a target direction detection result when the other moving body position detection method according to the first embodiment of the present invention is applied to a frequency of 5 kHz.
  • FIG. 16 shows a target direction detection result when the other moving body position detection method according to the first embodiment of the present invention is applied to a frequency of 6 kHz.
  • FIG. 17 shows a target direction detection result when the other moving body position detection method according to the first embodiment of the present invention is applied to a frequency of 7 kHz.
  • FIG. 18 is a block diagram illustrating a basic configuration of the other moving body position detection apparatus according to the second embodiment of the present invention.
  • FIG. 19 is a flowchart for explaining the other moving body position detection method according to the second embodiment of the present invention.
  • the other moving body position detection apparatus is mounted on a moving body (self-moving body) such as a vehicle, and is generated from a target existing around the moving body (other movement). Body) Based on the generated sound, the relative position of the object is detected.
  • the object to be detected is a moving body, for example, a vehicle approaching the moving body.
  • the other moving body position detection device inputs a surrounding sound wave, converts the input sound wave into a discrete signal, and outputs the sound wave input unit 10.
  • the processing unit 20 for processing various calculations performed by the other mobile object position detection apparatus according to the embodiment, the storage unit 30 for storing various data including program files, and the like according to the first embodiment
  • a traveling state detection unit 40 that detects a state (running state) of the moving body on which the moving body position detection device is mounted.
  • the sound wave input unit 10 indicates the sound wave detected by the sensor units 11-1 and 11-n (n: positive integer) that detects the sound wave and the sensor units 11-1 and 11-n.
  • An amplifier 12 for amplifying the signal and an AD converter 13 for A / D converting and discretizing the signal amplified by the amplifier 12 are provided.
  • the sensor units 11-1 and 11-n are composed of acoustic devices such as a microphone and a hydrophone, for example.
  • a plurality of sensor units 11-1 and 11-n are provided in order to obtain a gradient of sound pressure of sound waves to be detected (spatial differential of sound pressure).
  • the number of sensor units 11-1 and 11-n need not be plural, and may be single.
  • the sound wave input by the sound wave input unit 10 includes stationary noise and target generated sound generated from a target existing around.
  • the sound wave input unit 10 outputs a sound wave signal, which is an electric signal indicating the input sound wave, to the processing unit 20.
  • the processing unit 20 includes a sound wave signal processing unit 21 that processes a sound wave signal output from the sound wave input unit 10 and a sound wave input by the sound wave input unit 10 based on the sound wave signal processed by the sound wave signal processing unit 21.
  • a steady state determination unit 22 that determines whether or not a state is present, and a sound pressure of a sound wave input by the sound wave input unit 10, a time derivative of the sound pressure, and an element of a covariance matrix based on a spatial differential of the sound pressure,
  • a covariance processing unit 23 that calculates a first parameter for a sound wave that is determined not to be in a steady state and a second parameter for a sound wave that is determined to be in a steady state, and subtracts the second parameter from the first parameter
  • the target parameter calculation unit 24 that calculates the third parameter of the covariance matrix element based on the sound pressure of the target generated sound, the temporal differentiation of the sound pressure, and the spatial differentiation of the sound pressure, and the third parameter Includes a direction detection unit 25 to detect
  • the first parameter calculated by the covariance processing unit 23 is a parameter based on a sound wave including a stationary noise such as a sound generated from the moving body itself and a non-stationary target generated sound.
  • the second parameter is a parameter based on stationary noise such as sound generated from the moving body itself.
  • the storage unit 30 is a covariance matrix storage unit 31 that stores the second parameter calculated by the covariance processing unit 23, and a mobile unit information storage that stores information about the mobile unit such as tire information when the mobile unit is a vehicle.
  • Unit 32 and a map information storage unit 33 that stores an environment corresponding to the current position on the map.
  • the storage unit 30 includes a storage device such as a semiconductor memory or a hard disk device, for example.
  • the traveling state detector 40 includes a moving state detector 41 that detects the moving state of the moving body, a moving environment detector 42 that detects the environment around the moving body, and a position detector 43 that detects the position of the moving body.
  • the moving state detection unit 41 is connected to, for example, a CAN (Controller Area Network) or the like, and detects information indicating the moving state of the moving body such as a speed, an engine speed, and a gear ratio when the moving body is an automobile, for example. .
  • the moving environment detection unit 42 detects information indicating the environment, such as a wall and an overhead around the moving body.
  • the position detection unit 43 includes, for example, a global positioning system (GPS) receiver.
  • GPS global positioning system
  • the storage processing unit 26 of the processing unit 20 stores the second parameter calculated by the covariance processing unit 23 in the covariance matrix storage unit 31.
  • the second parameter stored in the covariance storage unit 31 may be calculated and stored at any time during the movement of the moving body, and a plurality of types of second parameters corresponding to the state of the moving body are stored in advance. You may do it.
  • the read processing unit 27 reads the second parameter stored in the covariance matrix storage unit 31.
  • the target parameter calculation unit 24 calculates the third parameter using the second parameter read from the covariance matrix storage unit 31 by the read processing unit 27.
  • the processing unit 20, the storage unit 30, and the traveling state detection unit 40 shown in FIG. 1 are each displayed as a logical structure, and the respective units constituting the processing unit 20, the storage unit 30, and the traveling state detection unit 40 are the same. It may be configured by an arithmetic processing unit that is hardware, or may be configured by separate hardware.
  • n x , n y , and n z are elements of a unit vector in the target direction that becomes a sound source from the center of the sensor unit 11 that becomes an observation point.
  • R represents the distance from the observation point to the sound source
  • C represents the speed of sound as a function of temperature.
  • the position of the sound source can be calculated by acquiring the sound pressure at the observation point at any time, the time differential of the sound pressure, the spatial differential of the sound pressure, and applying the wave source-constrained partial differential equation. For example, an input time-domain sound wave signal is decomposed into frames by applying a window function with an appropriate time interval. Thereafter, the direction of the sound source is estimated using a sound wave signal converted into the frequency domain by short-time Fourier transform.
  • n x is an element of the vector n, n y, any one of the n x Motomare.
  • Equation (4) is modified to obtain nx and distance R that minimize the square error of equation (7).
  • equations (8) to (13) the sum is calculated for all the obtained frequency bands by the short-time Fourier transform, and the only direction estimation result is calculated for an arbitrary time interval. .
  • the results of the equations (14) and (15) it is possible to obtain the direction estimation result for each frequency by calculating the equations (8) to (13) for each frequency instead of the sum.
  • the other mobile object position detection apparatus uses an algorithm for removing additive noise in the process of performing the spatiotemporal gradient method for a short time frame.
  • Expression (7) the result calculated for the time-frequency frame of the short-time Fourier transform using the window function can be expressed as Expression (16).
  • Expression (16) is not only a function of the frequency ⁇ but also depends on the time interval in which the integration is performed. That is, it can be regarded as an expression in the time-frequency domain of the wave source-constrained partial differential equation.
  • the parameters S, S tt , S xx , S t , S x , S xt calculated by the equations (8) to (13) are expressed by the equation (17) for the frame ⁇ set in an arbitrary section. It can be expressed as shown in Formula (22).
  • the parameters S, S tt , S xx , S t , S x , and S xt can be obtained for each frequency (that is, for each frequency bin that is half the FFT length used for Fourier transform).
  • the parameter S, S tt, S xx, S t, S x, S xt sets further shortened divided time may be short time obtained for each frame and, in the overall time-frequency short time frame On the other hand, one value may be calculated as an average value.
  • the sound pressure, the temporal differentiation of the sound pressure, and the spatial differentiation of the sound pressure can be expressed by the following vectors.
  • the signal detected at this time is a signal obtained by adding the sound pressure component F ( ⁇ , ⁇ ) coming from the target and the noise component U ( ⁇ , ⁇ ).
  • the short-time correlation at this time can be expressed as shown in Equation (25).
  • equation (25) can be expressed for equation (27).
  • the other moving body position detection apparatus uses the parameters shown in the equations (27) to (32) as the first parameters S, S tt , S xx , S t , S x , S xt. .
  • the first parameters S, S tt , S xx , S t , S x , and S xt are additively obtained by a signal based on sound waves generated from the object and a signal based on stationary noise in the spatiotemporal gradient covariance region. It means that they are superimposed.
  • the second parameters N, N tt , N xx , N t , N x , and N xt can be expressed as Equations (33) to (38). it can.
  • Expressions (39) to (44) mean that the third parameter excluding noise can be estimated.
  • the second parameter based on the noise signal is considered to have a substantially constant value. Therefore, by estimating the noise signal for each moving state in advance, the sound source whose position changes with time. On the other hand, the direction and distance of the sound source can be detected from the covariance matrix obtained for each time interval.
  • the third parameter may be calculated using the second parameter calculated in the frame ⁇ 1 immediately before the frame ⁇ in which the first parameter is calculated and mainly in which noise can be observed. good.
  • noise component removal algorithms which are the basic principle of the other mobile object position detection method according to the first embodiment, are called a covariance subtraction method.
  • the noise signal only needs to be stationary and does not necessarily satisfy the source-constrained partial differential equation. In other words, it may be effective against diffuse noise or noise that is not a point source such as that generated from a large area.
  • step S10 the other moving body position detection apparatus according to the first embodiment is initialized, and in step S20, the sound wave signal processing unit 21 converts the sound wave input by the sound wave input unit 10 into a discrete sound wave signal. Are input from the sound wave input unit 10 and processed.
  • the sound wave signal processing unit 21 detects, for example, in the sensor units 11-1 and 11-n included in the sound wave input unit 10, as shown in steps S110-1 and S110-n in FIG.
  • the signal processing is performed on the sound wave.
  • the sound wave signal processing unit 21 performs a short-time Fourier transform on a frame decomposed every short time by applying a window function such as a Hann window to the sound wave signal, and performs frequency domain signals (as a whole) for each frame. To time frequency domain signal).
  • the steady state determination unit 22 determines whether or not the sound wave input by the sound wave input unit 10 is in a steady state.
  • the steady state determination unit 22 acquires, for example, the sound pressure of the sound wave input by the sound wave input unit 10, the gradient of the sound pressure, the sound pressure for each frequency, the frequency gradient, and the like, and sets a predetermined threshold for these variances.
  • the continuity may be measured to determine whether or not the steady state is reached.
  • the steady state determination unit 22 estimates the presence or absence of an approaching vehicle by setting a predetermined threshold with respect to the magnitude of the variance of the direction detection result by the direction detection unit 25, and determines whether or not the vehicle is in a steady state. May be.
  • a threshold may be set for the addition average of the direction detection results to determine whether or not the steady state is reached.
  • step S312 the covariance processing unit 23 performs the second processing based on the steady noise as shown in equations (33) to (38).
  • step S313 the storage processing unit 26 stores the second parameter calculated by the covariance processing unit 23 in the covariance matrix storage unit 31.
  • the storage processing unit 26 stores the second parameter calculated from the immediately preceding frame to be calculated.
  • the storage processing unit 26 may store the second parameter calculated using the time frame ⁇ in which the signal is stationary noise (there is no target approaching the surroundings).
  • the storage processing unit 26 may store the second parameter corresponding to all noise patterns corresponding to the state of the moving body such as speed, gear ratio, tire information, and moving environment.
  • the map information is stored in advance in the map information storage unit 33 as the position of the wall, the elevated, etc., and based on the noise signal including the own vehicle running noise and the reflected sound measured in the environment corresponding to the stored wall.
  • the calculated second parameter may be stored. At this time, it is effective to use a map position uniquely determined by GPS or the like as a label.
  • step S311 the covariance processing unit 23 determines that the steady noise and the unsteady state are present in step S314 as shown in the equations (27) to (32).
  • First parameters S, S tt , S xx , S t , S x , S xt are calculated based on the sound wave composed of the target generated sound.
  • the calculation of the first parameter and the second parameter by the covariance processing unit 23 is performed based on the sound pressure (step S121) and the sound pressure from the sound wave signal processed by the sound wave signal processing unit 21, as shown in step S120 of FIG. This is performed after calculating time differentiation (step S122) and spatial differentiation of sound pressure (step S123).
  • step S315 of FIG. 4 the read processing unit 27 reads the second parameter from the covariance matrix storage unit 31.
  • the read processing unit 27 may read the second parameter stored in the covariance matrix storage unit 31 according to the state of the moving body detected by the traveling state detection unit 40.
  • step S40 the target parameter calculation unit 24 calculates the first parameter based on the target generated sound from the first and second parameters calculated by the covariance processing unit 23 as shown in the equations (39) to (44).
  • Three parameters S C , S C tt , S C xx , S C t , S C x , S C xt are calculated.
  • step S50 the direction detection unit 25 substitutes the third parameter calculated by the target parameter calculation unit 24 into the formulas (14) and (15) to calculate the target direction and the target. The distance is detected.
  • the above-mentioned covariance subtraction method was applied to data measured while driving on a public road of a demonstration vehicle equipped with another moving body position detection device.
  • the distance between the microphones serving as the sensor units is 2 cm.
  • the sampling frequency is 44.1 kHz
  • the frame length of the Fourier transform is 48 points
  • the frame shift is 24 points
  • the parameters related to the covariance matrix are obtained by averaging over 50 adjacent frames.
  • the surrounding environment of other vehicles during recording was confirmed by photographing the surroundings with a video camera at the same time.
  • FIGS. 6 to 11 show direction detection results when a normal spatiotemporal gradient method is applied for each frequency of 2 to 7 kHz.
  • 12 to 17 show direction detection results when processing by the covariance subtraction method is added.
  • N x the vertical axis represents the x component of the unit vector in the sound source direction, showing 1 backward, -1 forward.
  • the horizontal axis indicates the time when data was measured. The transition from the rear to the front of the plot indicates that another vehicle overtakes the adjacent lane.
  • the position detection method observes the magnitude of the variance of the direction detection result, and if the variance is larger than the predetermined threshold, there is no vehicle around. It can be used to determine the existence of nearby objects that are considered. Therefore, the direction detection result by the direction detection unit 25 may be used to determine whether or not the steady state determination unit 22 is in a steady state.
  • the detection result using the covariance subtraction method is wider than the detection result using only the spatiotemporal gradient method. Therefore, it can be seen that by using the covariance subtraction method, the influence of additive noise is reduced, the dynamic range of detection is improved, and as a result, the angle at which direction detection is possible increases.
  • the other mobile object position detection apparatus can detect the target position with high accuracy by reducing the influence of noise by subtracting additive noise in the region of the covariance matrix.
  • the moving state detection unit 41 by including the moving state detection unit 41, it is possible to appropriately reduce the influence of noise according to the moving affective body of the moving body.
  • the moving body position detection device by including the moving environment detection unit 42, it is possible to appropriately reduce the influence of noise according to the environment around the moving body.
  • the position detection unit 43 by including the position detection unit 43, it is possible to appropriately reduce the influence of noise according to the position of the moving body.
  • the sound wave signal processing part 21 can change the signal processing method of a sound wave signal by converting a sound wave signal into a frequency domain. .
  • the second parameter calculated by the sound wave signal input at a time before the sound wave signal used for calculating the first parameter is used.
  • the third parameter can be calculated using the second parameter stored in advance.
  • the storage unit 30 includes a sonic wave signal storage unit 34, and the storage processing unit 26 and the read processing unit 27 include sonic waves.
  • the second embodiment differs from the first embodiment in that an operation is performed on the signal storage unit 34.
  • Other configurations that are not described in the second embodiment are substantially the same as those in the first embodiment, and thus redundant description is omitted.
  • the storage processing unit 26 stores the second parameter calculated by the covariance processing unit 23 in the covariance matrix storage unit 31, and the readout processing unit 27 performs covariance for the third parameter calculation.
  • the storage processing unit 26 stores a sound wave signal based on stationary noise in the sound wave signal storage unit 34 using the flowchart of FIG.
  • a case where the covariance processing unit 23 calculates the first and second parameters after the reading processing unit 27 reads out the sound wave signal from the sound wave signal storage unit 34 will be described.
  • the processes other than step S32 shown in FIG. 19 are substantially the same as the processes other than step S31 shown in FIG.
  • step S321 the steady state determination unit 22 determines whether the sound wave input by the sound wave input unit 10 is in a steady state.
  • the steady state determination unit 22 acquires, for example, the sound pressure of the sound wave input by the sound wave input unit 10, the gradient of the sound pressure, the sound pressure for each frequency, the frequency gradient, and the like, and sets a predetermined threshold for these variances.
  • the continuity may be measured to determine whether or not the steady state is reached.
  • the presence or absence of an approaching vehicle may be estimated by setting a predetermined threshold for the magnitude of the variance of the direction detection result by the direction detection unit 25. Or you may make it take the addition average of a direction detection result.
  • step S322 the storage processing unit 26 stores the sound wave signal of the frame determined to be in the steady state in the sound wave signal storage unit 34.
  • the storage processing unit 26 may store the sound wave signal of the frame immediately before the frame determined to be in the steady state.
  • the storage processing unit 26 may store types of sound wave signals corresponding to all noise patterns corresponding to the state of the moving body such as speed, gear ratio, tire information, and moving environment.
  • the map information the position of a wall, an overpass or the like is stored in advance in the map information storage unit 33, and a sound wave signal indicating own vehicle running noise and reflected sound measured in an environment suitable for the stored wall is stored. You may make it leave. At this time, it is effective to use a map position uniquely determined by GPS or the like as a label.
  • the read processing unit 27 reads the sound wave signal from the sound wave signal storage unit 34 in step S323.
  • the read processing unit 27 may read the sound wave signal stored in the sound wave signal storage unit 34 in accordance with the state of the moving body detected by the traveling state detection unit 40.
  • the covariance processing unit 23 includes a stationary noise, the first parameter S based on sound waves comprising a non-stationary object generated sound, S tt, S xx, S t, S x, and S xt calculate. Further, the covariance processing unit 23 calculates the second parameters N, N tt , N xx , N t , N x , N xt based on the sound wave signal read by the reading processing unit 27 in step S323.
  • the other mobile object position detection apparatus can detect the target position with high accuracy by reducing the influence of noise by subtracting additive noise in the region of the covariance matrix.
  • the moving state detection unit 41 by including the moving state detection unit 41, it is possible to appropriately reduce the influence of noise according to the moving affective body of the moving body.
  • the other moving body position detection apparatus by including the moving environment detection unit 42, it is possible to appropriately reduce the influence of noise according to the environment around the moving body.
  • the position detection unit 43 by including the position detection unit 43, it is possible to appropriately reduce the influence of noise according to the position of the moving body.
  • the sound wave signal processing part 21 can change the signal processing method of a sound wave signal by converting a sound wave signal into a frequency domain. .
  • the second parameter calculated by the sound wave signal input at a time before the sound wave signal used for the calculation of the first parameter is used.
  • the third parameter can be calculated using the second parameter stored in advance.
  • the moving body on which the other moving body position detecting device is mounted is not limited to a vehicle, but can be applied to a helicopter, a ship, a submarine, and the like.
  • the method of detecting a symmetric position using the parameters of the covariance matrix has been described.
  • the parameters need not necessarily be calculated using a determinant.
  • the calculation may be omitted to the extent that the direction detection result can be regarded as substantially equivalent.
  • the moving environment detection unit 42 detects information indicating the environment, such as walls and overheads around the moving body, based on the detection result of the direction detection unit 25. You may make it do. For example, when there is a wall parallel to the moving direction of the moving body, the direction detection result by the direction detecting unit 25 is localized in a direction (angle) within a predetermined range. By setting these data in the moving environment detection unit 42 in advance, information indicating the environment around the moving body can be detected from the direction detection result by the direction detection unit 25.
  • the present invention it is possible to provide another mobile body position detection apparatus that can detect the target position by reducing the influence of noise by subtracting additive noise in the region of the covariance matrix. Therefore, the present invention has industrial applicability.

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Abstract

La présente invention concerne un dispositif comprenant : une unité d'entrée d'onde acoustique (10) qui entre une onde acoustique contenant un son généré par un objet en mouvement, le son étant généré par un bruit stationnaire et par le déplacement d'un objet en mouvement se trouvant aux alentours ; une unité d'évaluation d'état stationnaire (22) qui détermine si l'onde acoustique est stationnaire ; une unité de traitement par covariance (23) qui calcule un élément de matrice de covariance sur la base de la pression acoustique de l'onde acoustique, du différentiel temporel de la pression acoustique et du différentiel spatial de la pression acoustique, ledit élément de matrice de covariance étant calculé en tant que premier paramètre de l'onde acoustique quand il est déterminé que ladite onde acoustique n'est pas stationnaire par l'unité d'évaluation d'état stationnaire (22), ou étant calculé en tant que deuxième paramètre de l'onde acoustique quand il est déterminé que ladite onde acoustique est stationnaire par l'unité d'évaluation d'état stationnaire (22) ; une unité de calcul de paramètre d'objet en mouvement (24) qui soustrait le deuxième paramètre du premier paramètre, pour ainsi calculer, en tant que troisième paramètre, l'élément de matrice de covariance sur la base de la pression acoustique du son généré par un objet en mouvement, du différentiel temporel de la pression acoustique et du différentiel spatial de la pression acoustique ; et une unité de détection de direction (25) qui détecte la direction du corps en mouvement à partir du troisième paramètre.
PCT/JP2012/078623 2011-11-14 2012-11-05 Dispositif et procédé de détection de la position d'un objet en mouvement WO2013073399A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2017151221A (ja) * 2016-02-23 2017-08-31 日本電信電話株式会社 音源定位装置、方法、及びプログラム

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0592767U (ja) * 1992-05-18 1993-12-17 株式会社豊田中央研究所 接近車両認識装置
JP2010008474A (ja) * 2008-06-24 2010-01-14 National Institute Of Advanced Industrial & Technology 非日常音検出システム
WO2011001684A1 (fr) * 2009-07-02 2011-01-06 パナソニック株式会社 Dispositif de détection de la position d'un véhicule et procédé de détection de la position d'un véhicule
JP2011034435A (ja) * 2009-08-04 2011-02-17 Nissan Motor Co Ltd 車両位置演算装置及び車両位置演算方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0592767U (ja) * 1992-05-18 1993-12-17 株式会社豊田中央研究所 接近車両認識装置
JP2010008474A (ja) * 2008-06-24 2010-01-14 National Institute Of Advanced Industrial & Technology 非日常音検出システム
WO2011001684A1 (fr) * 2009-07-02 2011-01-06 パナソニック株式会社 Dispositif de détection de la position d'un véhicule et procédé de détection de la position d'un véhicule
JP2011034435A (ja) * 2009-08-04 2011-02-17 Nissan Motor Co Ltd 車両位置演算装置及び車両位置演算方法

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2017151221A (ja) * 2016-02-23 2017-08-31 日本電信電話株式会社 音源定位装置、方法、及びプログラム

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