Patent Publication Number: US-2022221582-A1

Title: Object detection device

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is based on and claims priority under 35 U.S.C. § 119 to Japanese Patent Application 2021-002370, filed on Jan. 8, 2021, the entire content of which is incorporated herein by reference. 
     TECHNICAL FIELD 
     This disclosure relates to an object detection device. 
     BACKGROUND DISCUSSION 
     In the related art, there is a technique for detecting information related to an object based on a transmission and reception of ultrasonic waves or the like. Further, in this technique, constant false alarm rate (CFAR) processing is known as processing for reducing noise, called clutter, which is generated due to a reflection by an object that is not a detection target. According to the CFAR processing, it is possible to acquire a CFAR signal corresponding to a signal obtained by removing the clutter from a processing target signal by using a moving average of a value (signal level) of the processing target signal based on a reception wave. 
     In general, transmission and reception waves (a transmission wave and a reception wave) are absorbed and attenuated due to a temperature and humidity of a medium through which the transmission wave and the reception wave propagate. Therefore, for example, in the related art, there is a technique that uses temperature data inside and outside a vehicle interior obtained from a temperature sensor and humidity data inside the vehicle interior obtained from a humidity sensor to estimate the humidity outside the vehicle interior and correct the absorption and the attenuation of the transmission and reception waves. According to this technique, even if there is no humidity sensor for detecting the humidity outside the vehicle interior, the correction can be performed. 
     Examples of the related art include JP 2018-115957A (Reference  1 ). 
     However, in the related art described above, since the humidity outside the vehicle interior is estimated based on the humidity inside the vehicle interior to correct the absorption and the attenuation, the accuracy may be low. Further, it would be meaningful if an absorption and attenuation value could be estimated with high accuracy in a case in which at least one of the temperature and the humidity of a target environment is not known in performing the correction and setting a threshold of a CFAR signal. 
     A need thus exists for an object detection device which is not susceptible to the drawback mentioned above. 
     SUMMARY 
     An object detection device according to an aspect of this disclosure includes: a transmitter configured to transmit a transmission wave to an outside including a road surface; a receiver configured to receive a reflected wave of the transmission wave being reflected by an object as a reception wave; a CFAR processor configured to acquire a CFAR signal at a predetermined detection timing by CFAR processing based on a value of a first processing target signal based on a reception wave received at the detection timing and an average value of values of second processing target signals based on the reception waves received in predetermined sections before and after the detection timing; and an estimator configured to estimate an absorption and attenuation value corresponding to the average value based on a road surface reflection estimation expression that defines a relation between the average value and the absorption and attenuation value in advance. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The foregoing and additional features and characteristics of this disclosure will become more apparent from the following detailed description considered with the reference to the accompanying drawings, wherein: 
         FIG. 1  is an exemplary and schematic diagram illustrating an appearance of a vehicle including an object detection system according to an embodiment when viewed from above; 
         FIG. 2  is an exemplary and schematic block diagram illustrating a hardware configuration of the object detection system according to the embodiment; 
         FIG. 3  is an exemplary and schematic diagram illustrating an outline of a technique used by an object detection device according to the embodiment to detect a distance to an object; 
         FIG. 4  is an exemplary and schematic block diagram illustrating functions of the object detection device according to the embodiment; 
         FIG. 5  is an exemplary and schematic diagram illustrating an example of CFAR processing that may be executed in the embodiment; 
         FIG. 6  is an exemplary and schematic diagram illustrating an example of a processing target signal and noise according to the embodiment; 
         FIG. 7  is an exemplary and schematic graph illustrating a relation between an amplitude and a distance related to a road surface reflection estimation expression according to the embodiment; and 
         FIG. 8  is an exemplary and schematic flowchart illustrating a series of processing executed by the object detection system according to the embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     Hereinafter, an embodiment and a modification disclosed here will be described with reference to the drawings. Configurations of the embodiment and the modification described below and actions and effects provided by the configurations are merely examples, and are not limited to the following description. 
     Embodiment 
       FIG. 1  is an exemplary and schematic view illustrating an appearance of a vehicle  1  including an object detection system according to an embodiment when viewed from above. 
     As described below, the object detection system according to the embodiment is an in-vehicle sensor system that performs a transmission and reception of a sound wave (ultrasonic wave) and acquires a time difference or the like of the transmission and reception, thereby detecting information related to an object (for example, an obstacle O illustrated in  FIG. 2  to be described later) including a person present around the object detection system. 
     More specifically, as illustrated in  FIG. 1 , the object detection system according to the embodiment includes an electronic control unit (ECU)  100  as an in-vehicle control device and object detection devices  201  to  204  as in-vehicle sonars. The ECU  100  is mounted inside the four-wheel vehicle  1  including a pair of front wheels  3 F and a pair of rear wheels  3 R, and the object detection devices  201  to  204  are mounted on an exterior of the vehicle  1 . 
     In the example illustrated in  FIG. 1 , as an example, the object detection devices  201  to  204  are installed at different positions on a rear end portion (rear bumper) of a vehicle body  2  as the exterior of the vehicle  1 , but the installation positions of the object detection devices  201  to  204  are not limited to the example illustrated in  FIG. 1 . For example, the object detection devices  201  to  204  may be installed on a front end portion (front bumper) of the vehicle body  2 , may be installed on a side surface portion of the vehicle body  2 , or may be installed on two or more of the rear end portion, the front end portion, and the side surface portion. 
     Further, in the embodiment, hardware configurations and functions of the object detection devices  201  to  204  are the same as each other. Therefore, in the following description, the object detection devices  201  to  204  may be collectively referred to as an object detection device  200  for simplification of description. Further, in the embodiment, the number of object detection devices  200  is not limited to four as illustrated in  FIG. 1 . 
       FIG. 2  is an exemplary and schematic block diagram illustrating a hardware configuration of the object detection system according to the embodiment. 
     As illustrated in  FIG. 2 , the ECU  100  has a hardware configuration similar to that of a normal computer. More specifically, the ECU  100  includes an input and output device  110 , a storage device  120 , and a processor  130 . 
     The input and output device  110  is an interface for implementing the transmission and reception of information between the ECU  100  and an outside. For example, in the example illustrated in  FIG. 2 , communication partners of the ECU  100  are the object detection device  200  and a temperature sensor  50 . The temperature sensor  50  is mounted on the vehicle  1  so as to measure a temperature around the vehicle  1  (target environment). 
     The storage device  120  includes a main storage device such as a read only memory (ROM) or a random access memory (RAM), and/or an auxiliary storage device such as a hard disk drive (HDD) or a solid state drive (SSD). 
     The processor  130  manages various processing executed by the ECU  100 . The processor  130  includes an arithmetic unit, for example, a central processing unit (CPU), and the like. The processor  130  reads and executes a computer program stored in the storage device  120 , thereby implementing various functions, for example, automatic parking, and the like. 
     As illustrated in  FIG. 2 , the object detection device  200  includes a transceiver  210  and a controller  220 . 
     The transceiver  210  includes a vibrator  211  including a piezoelectric element or the like, and the transmission and reception of the ultrasonic wave is implemented by the vibrator  211 . 
     More specifically, the transceiver  210  transmits, as a transmission wave, an ultrasonic wave generated in accordance with a vibration of the vibrator  211 , and receives, as a reception wave, the vibration of the vibrator  211  caused by the ultrasonic wave transmitted as the transmission wave being reflected by an object present outside and returned. In the example illustrated in  FIG. 2 , the obstacle O installed on a road surface RS is illustrated as the object that reflects the ultrasonic wave from the transceiver  210 . 
     In the example illustrated in  FIG. 2 , a configuration in which both the transmission of the transmission wave and the reception of the reception wave are implemented by the single transceiver  210  including the single vibrator  211  is illustrated. However, the technique of the embodiment is also applicable to a configuration in which a configuration on a transmission side and a configuration on a reception side are separated, for example, a configuration in which a first vibrator for transmitting the transmission wave and a second vibrator for receiving the reception wave are separately installed. 
     The controller  220  has a hardware configuration similar to that of a normal computer. More specifically, the controller  220  includes an input and output device  221 , a storage device  222 , and a processor  223 . 
     The input and output device  221  is an interface for implementing the transmission and reception of information between the controller  220  and an outside (the ECU  100  and the transceiver  210  in the example illustrated in  FIG. 1 ). 
     The storage device  222  includes a main storage device such as a ROM or a RAM, and/or an auxiliary storage device such as an HDD or an SSD. 
     The processor  223  manages various processing executed by the controller  220 . The processor  223  includes an arithmetic unit, for example, a CPU, and the like. The processor  223  reads and executes a computer program stored in a storage device  333 , thereby implementing various functions. 
     Here, the object detection device  200  according to the embodiment detects a distance to the object by a technique referred to as a time of flight (TOF) method. As described in detail below, the TOF method is a technique of calculating a distance to the object in consideration of a difference between a timing at which the transmission wave is transmitted (more specifically, the transmission is started) and a timing at which the reception wave is received (more specifically, the reception is started). 
       FIG. 3  is an exemplary and schematic diagram illustrating an outline of a technique used by the object detection device  200  according to the embodiment to detect a distance to the object. 
     More specifically,  FIG. 3  is an exemplary and schematic diagram represented in a graph form that illustrates a temporal change in a signal level (for example, amplitude) of the ultrasonic wave transmitted and received by the object detection device  200  according to the embodiment. In the graph illustrated in  FIG. 3 , a horizontal axis corresponds to a time, and a vertical axis corresponds to a signal level of a signal transmitted and received by the object detection device  200  via the transceiver  210  (the vibrator  211 ). 
     In the graph illustrated in  FIG. 3 , a solid line L 11  represents an example of an envelope curve representing a temporal change in the signal level of the signal transmitted and received by the object detection device  200 , that is, a vibration degree of the vibrator  211 . It can be seen from the solid line L 11  that by driving and vibrating the vibrator  211  for a time Ta from a timing t 0 , the transmission of the transmission wave is completed at a timing t 1 , and then during a time Tb until a timing t 2 , the vibration of the vibrator  211  due to inertia continues while attenuating. Therefore, in the graph illustrated in  FIG. 3 , the time Tb corresponds to a so-called reverberation time. 
     The solid line L 11  reaches a peak at which the vibration degree of the vibrator  211  exceeds (or equal to or more than) a predetermined threshold Th 1  represented by a one-dot chain line L 21  at a timing t 4  at which a time Tp elapses from the timing t 0  at which the transmission of the transmission wave is started. The threshold Th 1  is a value set in advance for identifying whether the vibration of the vibrator  211  is caused by a reception of a reception wave serving as a transmission wave reflected by a detection target object (for example, the obstacle O illustrated in  FIG. 2 ) and returned or is caused by a reception of a reception wave serving as a transmission wave reflected by a non-detection target object (for example, the road surface RS illustrated in  FIG. 2 ) and returned. 
       FIG. 3  illustrates an example in which the threshold Th 1  is set as a constant value that does not change as the time elapses, but in the embodiment, the threshold Th 1  may be set as a value that changes as the time elapses. 
     Here, the vibration having a peak exceeding (or equal to or more than) the threshold Th 1  can be considered to be caused by the reception of the reception wave serving as the transmission wave reflected by the detection target object and returned. On the other hand, the vibration having a peak equal to or lower than (or less than) the threshold Th 1  can be considered to be caused by the reception of the reception wave serving as the transmission wave reflected by the non-detection target object and returned. 
     Therefore, based on the solid line L 11 , it can be seen that the vibration of the vibrator  211  at the timing t 4  is caused by the reception of the reception wave serving as the transmission wave reflected by the detection target object and returned. 
     Further, in the solid line L 11 , the vibration of the vibrator  211  is attenuated after the timing t 4 . Therefore, the timing t 4  corresponds to a timing at which the reception of the reception wave serving as the transmission wave reflected by the detection target object and returned is completed, in other words, a timing at which the transmission wave last transmitted at the timing t 1  returns as the reception wave. 
     Further, in the solid line L 11 , a timing t 3  as a start point of the peak at the timing t 4  corresponds to a timing at which the reception of the reception wave serving as the transmission wave reflected by the detection target object and returned is started, in other words, a timing at which the transmission wave first transmitted at the timing t 0  returns as the reception wave. Therefore, in the solid line L 11 , a time ΔT between the timing t 3  and the timing t 4  is equal to the time Ta as a transmission time of the transmission wave. 
     Based on the above, in order to obtain a distance to the detection target object by the TOF method, it is necessary to obtain a time Tf between the timing t 0  at which the transmission wave starts to be transmitted and the timing t 3  at which the reception wave starts to be received. The time Tf can be obtained by subtracting the time ΔT equal to the time Ta as the transmission time of the transmission wave from the time Tp as a difference between the timing t 0  and the timing t 4  at which the signal level of the reception wave reaches the peak exceeding the threshold Th 1 . 
     The timing t 0  at which the transmission wave starts to be transmitted can be easily specified as a timing at which the object detection device  200  starts to operate, and the time Ta as the transmission time of the transmission wave is determined in advance by setting or the like. Therefore, in order to obtain the distance to the detection target object by the TOF method, it is important to specify the timing t 4  at which the signal level of the reception wave reaches the peak exceeding the threshold Th 1 . In order to specify the timing t 4 , it is important to accurately detect a correspondence between the transmission wave and the reception wave serving as the transmission wave reflected by the detection target object and returned. 
     Further, as described above, in general, the transmission and reception waves are absorbed and attenuated due to a temperature and humidity of a medium through which the transmission wave and the reception wave propagate. Therefore, for example, in the related art, there is a technique that uses temperature data inside and outside a vehicle interior from a temperature sensor and humidity data inside the vehicle interior from a humidity sensor to estimate the humidity outside the vehicle interior and correct the absorption and the attenuation of the transmission and reception waves. According to this technique, even if there is no humidity sensor for detecting the humidity outside the vehicle interior, the correction can be performed. 
     However, in the related art described above, since the humidity outside the vehicle interior is estimated based on the humidity inside the vehicle interior to correct the absorption and the attenuation, the accuracy may be low. Further, it would be meaningful if an absorption and attenuation value could be estimated with high accuracy in a case in which at least one of the temperature and the humidity of a target environment is not known in performing the correction and setting a threshold of a CFAR signal. 
     Therefore, in the embodiment, the object detection device  200  is configured as described below, and thus the absorption and attenuation value can be estimated with high accuracy in a case of performing CFAR processing. Hereinafter, the object detection device  200  will be described in detail. 
       FIG. 4  is an exemplary and schematic block diagram illustrating a detailed configuration of the object detection device  200  according to the embodiment. 
     In  FIG. 4 , the configuration on the transmission side and the configuration on the reception side are illustrated in a separated state, but such an aspect illustrated in the drawing is merely for convenience of description. Therefore, in the embodiment, as described above, both the transmission of the transmission wave and the reception of the reception wave are implemented by the single transceiver  210 . However, as described above, the technique of the embodiment is also applicable to the configuration in which the configuration on the transmission side and the configuration on the reception side are separated from each other. 
     As illustrated in  FIG. 4 , the object detection device  200  includes a transmitter  411  as a configuration on the transmission side. Further, the object detection device  200  includes, as a configuration on the reception side, a receiver  421 , a preprocessor  422 , a CFAR processor  423 , a threshold processor  424 , a detection processor  425 , and an estimator  426 . 
     Further, in the embodiment, at least a part of the configurations illustrated in  FIG. 4  may be implemented as a result of a cooperation between hardware and software, more specifically, as a result of the processor  223  of the object detection device  200  reading the computer program from the storage device  222  and executing the computer program. However, in the embodiment, at least a part of the configurations illustrated in  FIG. 4  may be implemented by dedicated hardware (circuitry). Further, in the embodiment, each configuration illustrated in  FIG. 4  may operate under a control of the controller  220  of the object detection device  200  itself, or may operate under a control of the external ECU  100 . 
     First, the configuration on the transmission side will be described. 
     The transmitter  411  transmits a transmission wave to an outside including a road surface by vibrating the vibrator  211  described above at a predetermined transmission interval. The transmission interval is a time interval from the transmission of the transmission wave to a next transmission of the transmission wave. The transmitter  411  is configured by using, for example, a circuit that generates a carrier wave, a circuit that generates a pulse signal corresponding to identification information to be given to the carrier wave, a multiplier that modulates the carrier wave according to the pulse signal, an amplifier that amplifies a transmission signal output from the multiplier, and the like. 
     Next, the configuration on the reception side will be described. 
     The receiver  421  receives a reflected wave obtained when the transmission wave transmitted from the transmitter  411  is reflected by the object as the reception wave, until a predetermined measurement time elapses after the transmission wave is transmitted. The measurement time is a standby time set for receiving the reception wave serving as the reflected wave of the transmission wave after the transmission wave is transmitted. 
     The preprocessor  422  performs preprocessing for converting a reception signal corresponding to the reception wave received by the receiver  421  into a processing target signal to be input to the CFAR processor  423 . The preprocessing includes, for example, amplification processing of amplifying a reception signal corresponding to a reception wave, filter processing of reducing noise included in the amplified reception signal, correlation processing of acquiring a correlation value indicating a similarity degree between the transmission signal and the reception signal, envelope curve processing of generating a signal based on an envelope curve of a waveform indicating a temporal change of the correlation value as a processing target signal, and the like. 
     The CFAR processor  423  acquires the CFAR signal by performing the CFAR processing on the processing target signal output from the preprocessor  422 . As described above, the CFAR processing is processing of acquiring a CFAR signal corresponding to a signal obtained by removing the clutter from the processing target signal by using a moving average of a value (signal level) of the processing target signal. 
     For example, the CFAR processor  423  according to the embodiment acquires a CFAR signal with a configuration as illustrated in  FIG. 5 . 
       FIG. 5  is an exemplary and schematic diagram illustrating an example of CFAR processing that may be executed in the embodiment. 
     As illustrated in  FIG. 5 , in the CFAR processing, first, a processing target signal  510  is sampled at a predetermined time interval. Then, an arithmetic unit  511  of the CFAR processor  423  calculates a sum of values of the processing target signals for N samples corresponding to the reception waves received in a section T 51  that is present before a detection timing t 50 . Further, an arithmetic unit  512  of the CFAR processor  423  calculates a sum of values of the processing target signals for N samples corresponding to the reception waves received in a section T 52  that is present after the detection timing t 50 . 
     Then, an arithmetic unit  520  of the CFAR processor  423  adds the calculation results of the arithmetic units  511  and  512 . Then, an arithmetic unit  530  of the CFAR processor  423  divides the calculation result of the arithmetic unit  520  by  2 N which is a sum of the number N of samples of the processing target signals in the section T 51  and the number N of samples of the processing target signals in the section T 52 , and calculates an average value of the values of the processing target signals in both the sections T 51  and T 52 . 
     Then, an arithmetic unit  540  of the CFAR processor  423  subtracts the average value as the calculation result of the arithmetic unit  530  from the value of the processing target signal at the detection timing t 50  and acquires a CFAR signal  550 . 
     As described above, the CFAR processor  423  according to the embodiment samples the processing target signal based on the reception wave, and acquires a CFAR signal based on a difference between a value of a first processing target signal for (at least) one sample based on the reception wave received at a predetermined detection timing and an average value of values of second processing target signals for a plurality of samples based on the reception waves received in the predetermined sections T 51  and T 52  before and after the detection timing. 
     In the above description, as an example of the CFAR processing, the processing of acquiring the CFAR signal based on the difference between the value of the first processing target signal and the average value of the values of the second processing target signals is illustrated. However, the CFAR processing according to the embodiment may be processing of acquiring a CFAR signal based on a ratio between the value of the first processing target signal and the average value of the values of the second processing target signals, or may be processing of acquiring a CFAR signal based on normalization of the difference between the value of the first processing target signal and the average value of the values of the second processing target signals. 
     Here, as described above, the CFAR signal corresponds to a signal obtained by removing the clutter from a processing target signal. More specifically, the CFAR signal corresponds to a signal obtained by removing various kinds of noise including the clutter and stationary noise generated stationarily in the transceiver  210  from the processing target signal. The processing target signal and the noise (clutter and stationary noise) are illustrated as waveforms as illustrated in  FIG. 6  below, for example. 
       FIG. 6  is an exemplary and schematic diagram illustrating an example of the processing target signal and noise according to the embodiment. 
     In the example illustrated in  FIG. 6 , a solid line L 601  represents a temporal change of the value of the processing target signal, a one-dot chain line L 602  represents a temporal change of the value of the clutter, and a two-dot chain line L 603  represents a temporal change of the value of the stationary noise. 
     As illustrated in  FIG. 6 , a magnitude relation between the values of the clutter (see the one-dot chain line L 602 ) and the stationary noise (see the two-dot chain line L 603 ) changes for each section. For example, in the example illustrated in  FIG. 6 , the value of the stationary noise is larger than the value of the clutter in a section T 61 , the value of the clutter is larger than the value of the stationary noise in a section T 62  next to the section T 61 , and the value of the stationary noise is larger than the value of the clutter in a section T 63  next to the section T 62 . 
     Further, a timing at which the value of the clutter increases is substantially determined in advance in accordance with an installation position and an installation attitude of the transceiver  210 . The value of the stationary noise is also substantially determined in advance. Therefore, the sections T 61  to T 63  are substantially determined in advance in accordance with the installation position and the installation attitude of the transceiver  210 . Further, a start point of the section T 61  coincides with a start point of the measurement time described above as the standby time of the receiver  421  set for receiving the reception wave serving as the reflected wave of the transmission wave, and an end point of the section T 63  coincides with an end point of the measurement time described above. 
     Here, in the sections T 61  and T 63 , since the clutter is negligibly small with respect to the processing target signal, the CFAR signal corresponding to the signal obtained by removing the clutter and the stationary noise from the processing target signal is a signal including the influences of the absorption and the attenuation of the processing target signal without including the influences of the absorption and the attenuation of the clutter. On the other hand, in the section T 62 , since the clutter is too large to be negligible with respect to the processing target signal, the CFAR signal is a signal that does not include the influences of the absorption and the attenuation because the influences of the absorption and the attenuation of the clutter and the influences of the absorption and the attenuation of the processing target signal cancel each other out. 
     Then, the detection processor  425  specifies a detection timing at which the value of the CFAR signal exceeds the threshold based on a comparison between the value of the CFAR signal and the threshold set by the threshold processor  424 . Since the detection timing at which the value of the CFAR signal exceeds the threshold coincides with a timing at which the signal level of the reception wave serving as the transmission wave reflected by the object and returned reaches a peak, when the detection timing at which the value of the CFAR signal exceeds the threshold is specified, the distance to the object can be detected by the TOF method described above. 
     Returning to  FIG. 4 , the estimator  426  estimates the absorption and attenuation value corresponding to the average value based on a road surface reflection estimation expression that defines a relation between the average value and the absorption and attenuation value in advance. A road surface reflection estimation expression A is expressed by, for example, the following Equation (1). 
         A=f (α,β)  (1)
 
     Here, α is a parameter indicating the absorption, and attenuation value. β is a parameter indicating a magnification in a direction of the amplitude (signal level). f(α, β) is a functional expression having two parameters of α and β, which is created in advance based on experimental results and the like, and includes, for example, an exponential function and a logarithmic function. 
     Further, the estimator  426  may correct the absorption and attenuation value based on the distance characteristic expression that defines the relation between the absorption and attenuation value and the distance in advance. The distance characteristic expression is created in advance based on experimental results and the like. 
     Further, for example, in the example of  FIG. 6 , it is preferable that the processing performed by the estimator  426  be performed on the section T 62  in which the clutter is too large to be negligible with respect to the processing target signal among the sections T 61  to T 63 , but the processing is not limited thereto. 
       FIG. 7  is an exemplary and schematic graph illustrating a relation between an amplitude and a distance related to a road surface reflection estimation expression according to the embodiment. In the graph of  FIG. 7 , a vertical axis represents an amplitude (signal level), and a horizontal axis represents a distance. A line L 1  corresponds to a case where a (absorption and attenuation value)=1. A line L 2  corresponds to a case where α=1.2. A line L 3  corresponds to a case where α=1.4. A line L 4  corresponds to a case where α=1.6. 
     Then, assuming that the result of performing the processing based on the road surface reflection estimation expression by the estimator  426  is the line L 11 , α=1.1 can be determined (estimated). 
     The relation between the absorption and attenuation value, the temperature, and the humidity is known. Therefore, when two values of these three values are known, the remaining one value can be calculated. That is, when the absorption and attenuation value is determined, for example, the processor  223  (calculator) can calculate the humidity of the target environment based on the absorption and attenuation value and the temperature data detected by the temperature sensor that detects the temperature of the target environment. Similarly, the temperature can be calculated based on the absorption and attenuation value and the humidity. 
     The threshold processor  424  sets the threshold for the CFAR signal by using the absorption and attenuation value estimated by the estimator  426 . 
       FIG. 8  is an exemplary and schematic flowchart illustrating a series of processing executed by the object detection system according to the embodiment. 
     As illustrated in  FIG. 8 , in the embodiment, first, in S 801 , the transmitter  411  of the object detection device  200  transmits a transmission wave. 
     Then, in S 802 , the receiver  421  of the object detection device  200  receives a reception wave corresponding to the transmission wave transmitted in S 801 . 
     Then, in S 803 , the preprocessor  422  of the object detection device  200  executes preprocessing for next processing in S 804  on a reception signal corresponding to the reception wave received in S 802 . 
     Then, in S 804 , the CFAR processor  423  of the object detection device  200  executes CFAR processing on the processing target signal output from the preprocessor  422  through the preprocessing in S 803 , and generates a CFAR signal. 
     Next, in S 805 , the estimator  426  estimates an absorption and attenuation value corresponding to the average value based on the road surface reflection estimation expression. Further, the estimator  426  may further correct the absorption and attenuation value based on the distance characteristic expression. 
     Next, in S 806 , the threshold processor  424  of the object detection device  200  sets a threshold for the CFAR signal generated in S 804  by using the absorption and attenuation value estimated in S 805 . 
     Then, in S 807 , the detection processor  425  of the object detection device  200  detects a distance to an object based on the comparison between a value of the CFAR signal and the threshold set in S 805 . Then, the processing ends. 
     As described above, according to the object detection device  200  of the embodiment, in a case of performing the CFAR processing, the absorption and attenuation value corresponding to the average value can be estimated with high accuracy based on the road surface reflection estimation expression. 
     Further, the absorption and attenuation value can be corrected to a more accurate value based on the distance characteristic expression. 
     Further, when temperature data exists, the humidity can be calculated with high accuracy based on the temperature data and the absorption and attenuation value. 
     Therefore, it is not necessary to use a worst value as the absorption and attenuation value as in the related art, and the humidity estimation, the threshold setting of the CFAR signal, the distance measurement, and the like can be performed with high accuracy by using the absorption and attenuation value estimated with high accuracy. Further, the absorption and attenuation value can also be applied to correct the absorption and attenuation at a time of identifying steps on the road surface. 
     &lt;Modification&gt; 
     In the embodiment described above, the technique disclosed here is applied to a configuration in which a distance to an object is detected by a transmission and reception of an ultrasonic wave. However, the technique disclosed here can also be applied to a configuration in which a distance to an object is detected by a transmission and reception of a wave other than the ultrasonic wave, such as a sound wave, a millimeter wave, a radar, and an electromagnetic wave. 
     An object detection device according to an aspect of this disclosure includes: a transmitter configured to transmit a transmission wave to an outside including a road surface; a receiver configured to receive a reflected wave of the transmission wave being reflected by an object as a reception wave; a CFAR processor configured to acquire a CFAR signal at a predetermined detection timing by CFAR processing based on a value of a first processing target signal based on a reception wave received at the detection timing and an average value of values of second processing target signals based on the reception waves received in predetermined sections before and after the detection timing; and an estimator configured to estimate an absorption and attenuation value corresponding to the average value based on a road surface reflection estimation expression that defines a relation between the average value and the absorption and attenuation value in advance. 
     With such a configuration, in a case of performing the CFAR processing, the absorption and attenuation value corresponding to the average value can be estimated with high accuracy based on the road surface reflection estimation expression. 
     Further, in the object detection device described above, the estimator may further correct the absorption and attenuation value based on a distance characteristic expression that defines a relation between the absorption and attenuation value and a distance in advance. 
     With such a configuration, the absorption and attenuation value can be corrected to a more accurate value based on the distance characteristic expression. 
     The object detection device may further include a calculator configured to calculate humidity of a target environment based on the absorption and attenuation value and temperature data detected by a temperature sensor configured to detect a temperature of the target environment. 
     With such a configuration, when temperature data exists, the humidity can be calculated with high accuracy based on the temperature data and the absorption and attenuation value. 
     While embodiments and modifications disclosed here have been described, these embodiments and modifications have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, these embodiments and modifications described herein may be embodied in a variety of forms; furthermore, various omissions, substitutions and changes in the form of these embodiments and modifications described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions. 
     The principles, preferred embodiment and mode of operation of the present invention have been described in the foregoing specification. However, the invention which is intended to be protected is not to be construed as limited to the particular embodiments disclosed. Further, the embodiments described herein are to be regarded as illustrative rather than restrictive. Variations and changes may be made by others, and equivalents employed, without departing from the spirit of the present invention. Accordingly, it is expressly intended that all such variations, changes and equivalents which fall within the spirit and scope of the present invention as defined in the claims, be embraced thereby.