KR20210083147A - Object detection device and operating method of the same - Google Patents

Abstract

An object detection device converts each of a transmission signal and a reception signal into digital signals according to preset sampling periods, and performs interpolation between the sampling periods. In addition, the object detection device removes the noise of the interpolated signal, calculates a cross correlation signal of the noise-removed signal, and acquires a three-dimensional image based on the quality of the cross correlation signal. It is possible to reduce the probability of misdetection while increasing distance resolution.

Description

Object detection device and operating method of the same

The present disclosure relates to an object detection apparatus and an operating method thereof.

The object detection apparatus may generate a 3D image of an object by measuring a time of flight (ToF) of light. Specifically, the object detection apparatus calculates the distance to the object by measuring the time until the light signal emitted from the light source is reflected by the object and returns, and generates a depth image of the object based on the calculated distance. have.

Such an object detection device converts an optical signal into a digital signal to calculate the time-of-flight (ToF) of light, but the conventional object detection device converts the optical signal into a digital signal using only an analog-to-digital converter (ADC). Since it is converted, there is a problem that there is a constraint on the distance resolution. In addition, there is a problem in that the conventional object detection apparatus does not provide a solution for removing low frequency noise.

The present disclosure provides an object detection apparatus capable of reducing the possibility of false detection while increasing distance resolution and an operating method thereof.

The technical problem to be achieved by the present embodiment is not limited to the above technical problems, and other technical problems can be inferred from the following embodiments.

An object detection apparatus according to one aspect includes a converter for converting each of a transmission signal and a reception signal into a digital signal according to a preset sampling period, an interpolator for interpolating between the sampling periods, the interpolated transmission signal and a filter unit that removes noise from each of the interpolated received signals, and generates a cross correlation signal between the noise-removed transmission signal and the noise-removed reception signal, and generates a peak of the cross-correlation signal The control unit may include a control unit for obtaining a 3D image of the object based on the value.

A method of operating an object detection apparatus according to another aspect includes receiving a transmission signal irradiated toward an object and a reception signal reflected from the object, and converting each of the transmission signal and the reception signal into a digital signal according to a preset sampling period. converting, interpolating between the sampling periods, removing noise from each of the interpolated transmission signal and the interpolated reception signal, and the noise-removed transmission signal and the noise-removed reception signal The method may include generating a cross-correlation signal therebetween, and obtaining a three-dimensional image of the object based on a peak value of the cross-correlation signal.

1 is a diagram for explaining an exemplary operation of an object detection apparatus according to an embodiment.
2 is an internal block diagram of an apparatus for detecting an object according to an exemplary embodiment.
3 is a diagram for explaining a method of interpolating a transmission signal and a reception signal according to an embodiment.
4 is a diagram for explaining an effect of increasing distance resolution according to interpolation of a transmission signal and a reception signal.
5 is a diagram for explaining an effect of increasing distance resolution according to interpolation of a transmission signal and a reception signal.
6 is a view for explaining a method of removing low-frequency noise of a transmission signal and a reception signal according to an embodiment.
7 is a diagram for explaining an effect generated when a zero is inserted into a blank area of third input data.
8A to 8B are diagrams for explaining an effect of increasing a detection distance according to the removal of low-frequency noise of a transmission signal and a reception signal.
9 is a view for explaining an effect of increasing a detection distance according to the removal of low-frequency noise of a transmission signal and a reception signal.
10 is a diagram for explaining a method of calculating the quality of a cross-correlation signal according to an embodiment.
11 is a diagram for explaining an effect of preventing false detection according to a quality calculation of a cross-correlation signal.
12 is a flowchart illustrating an object detection method according to an embodiment.
13 is a flowchart for explaining the method of removing high-frequency noise of FIG. 12 .
14 is a flowchart for explaining the low-frequency noise removal method of FIG. 12 .
15 is a flowchart illustrating the 3D image acquisition method of FIG. 12 .

The appearances of the phrases "in some embodiments" or "in one embodiment" in various places in this specification are not necessarily all referring to the same embodiment.

Some embodiments of the present disclosure may be represented by functional block configurations and various processing steps. Some or all of these functional blocks may be implemented in various numbers of hardware and/or software configurations that perform specific functions. For example, the functional blocks of the present disclosure may be implemented by one or more microprocessors, or by circuit configurations for a given function. Also, for example, the functional blocks of the present disclosure may be implemented in various programming or scripting languages. The functional blocks may be implemented as an algorithm running on one or more processors. Also, the present disclosure may employ prior art for electronic configuration, signal processing, and/or data processing, and the like. Terms such as “mechanism”, “element”, “means” and “configuration” may be used broadly and are not limited to mechanical and physical components.

In addition, the connecting lines or connecting members between the components shown in the drawings only exemplify functional connections and/or physical or circuit connections. In an actual device, a connection between components may be represented by various functional connections, physical connections, or circuit connections that are replaceable or added.

1 is a diagram for explaining an exemplary operation of an object detection apparatus according to an embodiment.

Referring to the drawings, the object detection apparatus 100 includes a transmitter 110 that radiates a transmission signal S1 toward an object OBJ, and a receiver 120 that receives a reception signal S2 reflected from the object OBJ. and a controller 130 for controlling the transmitter 110 and the receiver 120 .

The object detecting apparatus 100 may be a 3D sensor that generates a 3D image of the object OBJ. For example, the object detection apparatus 100 may include a lidar (LiDAR), a radar (radar), and the like, but is not limited thereto.

The transmitter 110 may output light to be used for analysis of the position and shape of the object OBJ. For example, the transmitter 110 may output light of an infrared band wavelength. When the light in the infrared band is used, mixing with natural light in the visible light region including sunlight can be prevented. However, it is not necessarily limited to the infrared band and may emit light of various wavelength bands.

The transmitter 110 may include at least one light source. For example, the transmitter 110 includes a laser diode (LD), an edge emitting laser, a vertical-cavity surface emitting laser (VCSEL), a distributed feedback laser, It may include a light source such as a light emitting diode (LED) or a super luminescent diode (SLD).

The transmitter 110 may generate and output light of a plurality of different wavelength bands. Also, the transmitter 110 may generate and output pulsed light or continuous light. The light generated by the transmitter 110 may be irradiated toward the object OBJ as the transmission signal S1 .

According to an embodiment, the transmitter 110 may further include a beam steering element for changing the irradiation angle of the transmission signal S1. For example, the beam steering element may be a scanning mirror or an optical phased array.

The controller 130 may control the transmitter 110 to change the irradiation angle of the transmit signal S1 . The controller 130 may control the transmitter 110 so that the transmission signal S1 scans the entire object OBJ. In an embodiment, the controller 130 may control the transmitter 110 to scan the object OBJ at different irradiation angles with the transmission signal S1 output from each of the plurality of light sources. In another embodiment, the controller 130 may control the transmitter 110 so that the transmission signal S1 output from each of the plurality of light sources scans the object OBJ at the same irradiation angle.

The receiving unit 120 includes at least one light detecting element, and the light detecting element may distinguish and detect the received signal S2 reflected from the object OBJ. According to an embodiment, the receiver 120 may further include an optical element for collecting the received signal on a predetermined light detection element.

The light detection element is a sensor capable of sensing light, and may be, for example, a light receiving element that generates an electrical signal by light energy. The kind of light receiving element is not specifically limited.

The controller 130 may perform signal processing for obtaining information on the object OBJ by using the received signal detected by the receiver 120 . The controller 130 may determine a distance to the object OBJ based on the flight time of the light output by the transmitter 110 and perform data processing for analyzing the position and shape of the object OBJ. For example, the controller 130 may generate a point cloud based on distance information to the object OBJ, and may acquire a 3D image of the object OBJ based on the point cloud.

The 3D image obtained by the controller 130 may be transmitted to another unit and utilized. For example, such information may be transmitted to the control unit of an autonomous driving device such as an unmanned vehicle or a drone to which the object detection apparatus 100 is employed. In addition, such information may be utilized in smartphones, cell phones, personal digital assistants (PDAs), laptops, personal computers (PCs), wearable devices, and other mobile or non-mobile computing devices.

In addition, the controller 130 may control the overall operation of the object detection apparatus 100 including control of the transmitter 110 and the receiver 120 . For example, the controller 130 may perform power supply control, on/off control, pulse wave (PW) or continuous wave (CW) generation control, etc. for the transmitter 110 .

Meanwhile, the object detecting apparatus 100 of the present disclosure may further include other general-purpose components in addition to the components shown in FIG. 1 .

For example, the object detection apparatus 100 may further include a memory (not shown) for storing various data. The memory may store data processed by the object detection apparatus 100 and data to be processed. In addition, the memory may store applications, drivers, etc. to be driven by the object detection apparatus.

Memory includes random access memory (RAM), such as dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), CD-ROM, blue Ray or other optical disk storage, hard disk drive (HDD), solid state drive (SSD), or flash memory, and may further include other external storage devices that can be accessed by object detection apparatus 100 . have.

2 is an internal block diagram of an apparatus for detecting an object according to an exemplary embodiment.

Referring to the drawings, the object detection apparatus 100 may include a transmitter 110 , a receiver 120 , a converter 140 , an interpolator 150 , a filter unit 160 , and a controller 130 .

The transmitter 110 may output a transmission signal toward the object. Also, the transmitter 110 may output a portion of the transmission signal to the converter 140 . Part of the transmitted signal can be used to calculate the light's time-of-flight. The receiver 120 may receive the received signal reflected from the object. The transmitter 110 of FIG. 2 may correspond to the transmitter 110 of FIG. 1 , and the receiver 120 of FIG. 2 may correspond to the receiver 120 of FIG. 1 .

The converter 140 may convert each of the transmission signal and the reception signal into a digital signal according to a preset sampling period. For example, the sampling period may be set in the range of 100 Hz to 10 GHz. The converter 140 may output the digital signal as vector data in the form of a column vector or a row vector. Vector data may mean an array in the form of a column vector or a row vector consisting of a set of elements. In each element, quantized values of the transmission signal and the reception signal may be stored.

Specifically, the converter 140 may include a first analog-to-digital converter 141 and a second analog-to-digital converter 142 .

The first analog-to-digital converter 141 may convert the transmission signal into a first digital signal based on a preset sampling period. In other words, the first digital signal may be a converted transmission signal. The first analog-to-digital converter 141 may output the first digital signal in the form of a column vector or a row vector. A quantized value of a transmission signal according to a sampling period may be stored in each element.

The second analog-to-digital converter 142 may convert the received signal into a second digital signal based on a preset sampling period. In other words, the second digital signal may be a converted reception signal. The second analog-to-digital converter 142 may output the second digital signal in the form of a column vector or a row vector. A quantized value of a received signal according to a sampling period may be stored in each element.

The first analog-to-digital converter 141 may output the first digital signal to the first resampling unit 151 included in the interpolation unit 150 . The second analog-to-digital converter 142 may output the second digital signal to the second resampling unit 152 included in the interpolation unit 1510 .

The interpolator 150 may interpolate the first digital signal and the second digital signal by predicting an element between sampling periods. The interpolator 150 may interpolate between each element included in the vector data. For example, the interpolation unit 150 may include a linear interpolation method, a polynomial interpolation method, a spline interpolation method, an exponential interpolation method, and log-linear interpolation (log-linear). The first digital signal and the second digital signal are interpolated using at least one of an interpolation method, a Lagrange interpolation method, a Newton interpolation method, and a two-dimensional interpolation method. can do. However, the above-described interpolation method is only an example of the interpolation method, and various interpolation methods for interpolating the first digital signal and the second digital signal may be used.

The interpolator 150 may interpolate between sampling periods according to a preset interpolation period. The preset interpolation period may be set in the range of 2 to 20. In other words, the interpolator 150 may interpolate the first digital signal and the second digital signal by dividing the sampling period into 2 to 20 sections. For example, when the sampling period is 100 Hz, the interpolator 150 may interpolate the first digital signal and the second digital signal by predicting an element corresponding to 50 Hz.

The interpolation unit 150 may include a first resampling unit 151 and a second resampling unit 152 . The first resampling unit 151 may interpolate the first digital signal, and the second resampling unit 152 may interpolate the second digital signal.

The first resampling unit 151 may output the interpolated first digital signal to the filter unit 160 , and the second resampling unit 152 may output the interpolated second digital signal to the filter unit 160 .

Meanwhile, the interpolated first digital signal may be referred to as an interpolated transmission signal, and the interpolated second digital signal may be referred to as an interpolated reception signal.

Since the object detection apparatus 100 of the present disclosure increases a sampling rate through the interpolator 150 , a hardware design change (eg, a high sampling rate analog-to-digital converter is used) Even without it, there is an effect that the distance resolution is significantly increased.

The filter unit 160 may remove noise of each of the interpolated transmission signal and the interpolated reception signal. The filter unit 160 may remove high-frequency noise of the interpolated transmission signal and the interpolated reception signal. Also, the filter unit 160 may remove low-frequency noise of the interpolated transmission signal and the interpolated reception signal. To this end, the filter unit 160 may include a first noise removing unit 161 and a second noise removing unit 162 .

The first noise removing unit 161 may remove high-frequency noise of the interpolated transmission signal and the interpolated reception signal. According to an embodiment, the first noise removing unit 161 may remove only the high-frequency noise of the interpolated received signal.

Specifically, since the converting unit 140 outputs the transmitted signal and the received signal in the form of vector data, and the interpolating unit 150 interpolates between each element included in the vector data, the first noise removing unit 161 is The interpolated transmission signal may be received in the form of vector data.

The first noise removing unit 161 may accumulate each element included in the interpolated vector data for a preset time. Also, the first noise removing unit 161 may remove the high frequency noise by outputting an average value of the accumulated elements. In this case, the preset time may be 0.01 ms, but is not limited thereto.

For example, the first noise removing unit 161 receives the first row vector data and the second row vector data for a preset time, and elements included in the first row vector data are 2, 4, 7, and 9, respectively. , and when the elements included in the second row vector data are 3, 5, 4, and 9, respectively, the first noise removing unit 161 may obtain the accumulated row vector data having 5, 9, 11, and 18 as elements. can Also, the first noise removing unit 161 may output average row vector data having as elements 2.5, 4.5, 5.5, and 9, which are average values of the accumulated row vector data.

The high frequency noise of the interpolated transmission signal and the interpolated reception signal may be removed by the first noise removing unit 161 accumulating vector data for a preset time and outputting an average value of the vector data.

The second noise removing unit 162 may remove low-frequency noise of the interpolated transmission signal and the interpolated reception signal.

Specifically, the second noise removing unit 162 may receive vector data from which the high frequency noise is removed as the first input data. Also, the second noise removing unit 162 may generate the second input data by element-shifting each element included in the first input data by a preset direction and a preset size.

The preset direction may be any one of left, right, upper, and lower directions. When the vector data is a row vector, the preset direction may be set to the left or the right. In this case, the left side may mean a direction in which the column address of the vector data decreases, and the right side may indicate a direction in which the column address of the vector data increases. Also, when the vector data is a column vector, the preset direction may be set to the upper side or the lower side. In this case, the upper side may mean a direction in which the row address of the vector data decreases, and the lower side may indicate a direction in which the row address of the vector data increases. The preset size may be set to 500 elements.

The second noise removing unit 162 may output third input data from which low-frequency noise is removed by subtracting each element included in the second input data from each element included in the first input data.

Meanwhile, when generating the third input data from which the low frequency noise is removed, the second noise removing unit 162 may insert a zero into the blank area generated by the shift of the first input data. The third input data from which the low-frequency noise is removed may be provided to the cross-correlator 132 as the first digital signal from which the noise has been removed. In other words, the second noise removing unit 162 may remove the low-frequency noise of the interpolated first digital signal and output the noise-removed first digital signal to the cross-correlation unit 132 in the control unit 130 . Also, the second noise removing unit 162 may remove low-frequency noise of the interpolated second digital signal and output the noise-removed second digital signal to the cross-correlation unit 132 in the control unit 130 .

Meanwhile, the noise-removed first digital signal may be referred to as a noise-removed transmission signal, and the noise-removed second digital signal may be referred to as a noise-removed reception signal.

The object detection apparatus 100 of the present disclosure removes not only high-frequency noise of a transmission signal and a reception signal, but also low-frequency noise, so that the detection distance is remarkably increased.

The controller 130 may generate a cross correlation signal between the noise-removed transmission signal and the noise-removed reception signal. Also, the controller 130 may detect at least one peak value from the cross-correlation signal. Also, the controller 130 may determine the quality of the cross-correlation signal based on the peak value of the cross-correlation signal. Also, the controller 130 may acquire a 3D image of the object based on the quality of the cross-correlation signal. To this end, the controller 130 may include a cross-correlator 132 , a peak detector 133 , a quality calculator 134 , and a point cloud generator 135 .

The cross-correlator 132 may receive a noise-removed transmission signal and a noise-removed reception signal from the filter unit 160 .

The cross-correlation unit 132 may generate a cross-correlation signal between a noise-removed transmission signal and a noise-removed reception signal. To this end, the cross-correlator 132 may include a correlator. In an embodiment, the cross-correlation unit 132 may generate a cross-correlation signal by Equation 1 below.

In Equation 1, S1 may mean a transmission signal, S2 may mean a reception signal, and S3 may mean a cross-correlation signal.

The cross-correlation unit 132 may output a cross-correlation signal to the peak detector 133 .

The peak detector 133 may detect at least one peak value from the cross-correlation signal. The peak detector 133 may detect a first peak value having the largest absolute value among peak values of the cross-correlation signal. Also, the peak detector 133 may detect a second peak value having the largest absolute value among the remaining peak values except for the first peak value. The peak detector 133 may output the first peak value and the second peak value to the quality calculator 134 .

The quality calculator 134 may calculate the quality of the cross-correlation signal based on the absolute value of the first peak value and the absolute value of the second peak value.

The quality calculator 134 may provide quality information of the cross-correlation signal to the point cloud generator 135 .

The point cloud generator 135 may generate a point cloud based on the quality information of the cross-correlation signal. Also, the point cloud generator 135 may acquire a 3D image of the object based on the point cloud.

Specifically, the point cloud generator 135 may generate a point cloud based on a cross-correlation signal having a preset quality or higher. For example, the reference quality may be set to 2, but is not limited thereto.

The point cloud generator 135 may calculate the transmission time of the transmission signal and the reception time of the reception signal based on the first peak value of the cross-correlation signal of the reference quality or higher. In addition, the point cloud generator 135 may calculate the flight time of the light output from the transmitter 110 based on the transmission time and the reception time. Also, the point cloud generator 135 may calculate the distance to the object based on the flight time of the light. Also, the point cloud generator 135 may generate a three-dimensional point cloud based on distance information to the object.

On the other hand, the point cloud generator 135 may ignore the peak value of the cross-correlation signal less than the reference quality. Also, the point cloud generator 135 may map the maximum detection distance information to a point cloud corresponding to a cross-correlation signal of less than a reference quality. For example, when the maximum detection distance of the object detection apparatus 100 is 200 m, the point cloud generator 135 may uniformly store distance information of 200 m in the point cloud corresponding to the cross-correlation signal of less than the reference quality. .

Since the object detection apparatus 100 of the present disclosure generates a point cloud in consideration of the quality of the cross-correlation signal, it has an effect of remarkably reducing the possibility of false detection of an object.

Meanwhile, in FIG. 2 , the transform unit 140 , the interpolator 150 , and the filter unit 160 are shown as separate components separated from the control unit 130 , but according to an embodiment, the transform unit 140 and the interpolator unit 160 . 150 and the filter unit 160 may be included in the control unit 130 as a part of the control unit 130 . In addition, according to an embodiment, the cross-correlation unit 132 , the peak detection unit 133 , the quality calculation unit 134 , and the point cloud generation unit 135 in the control unit 130 are configured as separate components distinct from the control unit 130 . It might work.

3 is a diagram for explaining a method of interpolating a transmission signal and a reception signal according to an embodiment.

Referring to the drawings, the converter 140 may convert a transmission signal and a reception signal into vector data in the form of a column vector or a row vector and output the converted signal. 3 exemplifies that the transform unit 140 outputs the vector data 310 in the form of a row vector by the transmission signal and the received signal, but the following description is also applicable to vector data in the form of a row vector. In this case, the left direction and the right direction of the row vector may correspond to the upper direction and the lower direction of the column vector, respectively.

The interpolator 150 may interpolate the vector data 310 by predicting elements between sampling periods. Since each element of the vector data 310 stores quantized values of the transmission signal and the reception signal based on the sampling period, the interpolation unit 150 interpolates between the sampling periods means that the interpolator 150 is applied to the vector data. It may have the same meaning as the meaning of interpolating between each included element.

The interpolator 150 may interpolate between the first element E1 and the second element E2 of the vector data 310 .

Specifically, the interpolator 150 may calculate an average value of the values of the first element E1 and the second element E2 . The interpolator 150 uses an average value of the values of the first element E1 and the second element E2 as the first interpolation element E1 ′, between the first element E1 and the second element E2 . can be inserted. In addition, the interpolator 150 uses an average value of the values of the second element E2 and the third element E3 as the second interpolation element E2', and the second element E2 and the third element E3. can be inserted between them.

The interpolator 150 may interpolate between each element included in the vector data 310 through the above-described method. However, interpolation between each element through an average value is only an example and is not limited thereto. In other words, various interpolation methods for interpolating the vector data 310 may be used.

3 shows vector data 320 interpolated through any one of various interpolation methods.

As shown in FIG. 3 , the object detection apparatus 100 of the present disclosure has an effect of significantly increasing the sampling rates of the transmission signal and the reception signal without using an analog-to-digital converter having a high sampling rate.

Meanwhile, the interpolator 150 of the present disclosure is disposed between the transform unit 140 and the filter unit 160 , and interpolates the transmitted signal before the high frequency noise is removed and the received signal before the high frequency noise is removed.

When the interpolator 150 interpolates the transmitted signal before the high frequency noise is removed and the received signal before the high frequency noise is removed, the distance resolution of the object detection apparatus 100 is remarkably increased. The effect of increasing the distance resolution according to the interpolation of the transmitted signal and the received signal will be described in more detail with reference to FIGS. 4 to 5 .

FIG. 4 is a diagram for explaining an effect of increasing distance resolution according to interpolation of a transmission signal and a reception signal, and FIG. 5 is a diagram for explaining an effect of increasing distance resolution according to interpolation of a transmission signal and a reception signal.

For convenience of explanation, the effect of increasing the distance resolution is described with reference to the received signal in FIGS. 4 to 5 , but the following description may also be applied to the transmitted signal.

Referring to the drawings, the reception signals 410 are illustrated in FIG. 4 . When the object detecting apparatus 100 interpolates the received signal after removing the high frequency noise, the object detecting apparatus 100 may accumulate the received signals 410 . The first accumulated signal 420 accumulated by the object detecting apparatus 100 may be interpolated. Since the object detection apparatus 100 interpolates the accumulated first accumulated signal 420 while accumulating the received signals 410 , the interpolated first accumulated signal 430 includes a plurality of peak values Pk1 and Pk2 . may be included.

As shown in FIG. 4 , when the object detecting apparatus 100 interpolates the accumulated first accumulated signal 420 after accumulating the received signals 410 , the sampling rate is increased but the distance resolution is not increased. On the other hand, the object detection apparatus 100 of the present disclosure may increase the distance resolution by interpolating the received signal before removing the high-frequency noise.

Specifically, the object detection apparatus 100 of the present disclosure may interpolate each of the received signals 411 , 412 , 413 , and 414 . Also, the object detection apparatus 100 may accumulate each of the interpolated received signals 415 , 416 , 417 , and 418 . When the object detection apparatus 100 interpolates each of the received signals 411 , 412 , 413 , and 414 and then accumulates the interpolated received signals 415 , 416 , 417 , and 418 , the accumulated second accumulation Signal 440 may include one peak value Pk3.

As shown in FIG. 4 , when the object detection apparatus 100 interpolates each of the received signals 411 , 412 , 413 , and 414 , and then accumulates the interpolated received signals 415 , 416 , 417 , and 418 . , the distance to the object can be classified more precisely. In other words, the object detection apparatus 100 of the present disclosure interpolates each of the received signals 411 , 412 , 413 , and 414 , and then accumulates the interpolated received signals 415 , 416 , 417 and 418 , so the distance The resolution can be significantly increased.

5 shows a first distance resolution graph 510 and an object detection apparatus 100 when the object detection apparatus 100 interpolates the accumulated first accumulated signals 420 after accumulating the received signals 410 . After interpolating each of the received signals 411 , 412 , 413 , and 414 , a second distance resolution graph 520 is shown in the case of accumulating the interpolated received signals 415 , 416 , 417 , 418 . .

As shown in FIG. 5 , when the object detecting apparatus 100 interpolates the accumulated first accumulated signal 420 after accumulating the received signals 410 , it cannot distinguish a distance of 8 cm, whereas the object detecting apparatus ( 100) after interpolating each of the received signals 411, 412, 413, and 414, when accumulating the interpolated received signals 415, 416, 417, 418, it can be seen that a distance of 8 cm is also distinguished. . In other words, the object detection apparatus 100 of the present disclosure may significantly increase the distance resolution.

6 is a view for explaining a method of removing low-frequency noise of a transmission signal and a reception signal according to an embodiment.

Referring to the drawing, the second noise removing unit 162 may receive vector data from which the high frequency noise is removed as the first input data 610 .

The second noise removing unit 162 may generate the second input data 620 by shifting each element included in the first input data 610 by a preset direction and a preset size. When shifting an element, the second noise removing unit 162 may delete elements out of a column address range. Accordingly, the length of the second input data 620 may be shorter than the length of the first input data 610 .

Specifically, when the first input data 610 is in the form of a row vector, the second noise removing unit 162 may element-shift the first input data 610 left or right. In this case, the left side may mean a direction in which the column address of the row vector decreases, and the right side may indicate a direction in which the column address of the row vector increases. Also, the second noise removing unit 162 may element-shift the first input data 610 by 1 to 500 elements.

For example, as shown in FIG. 6 , the second noise removing unit 162 may generate the second input data 620 by shifting the first input data 610 in the left direction by 2 elements. In this case, the third element E ₃ included in the first input data 610 may be disposed in the first column of the second input data 620 by reducing the column address by two. Also, the first element E ₁ and the second element E ₂ outside the column address range may be deleted.

The second noise removing unit 162 subtracts each element included in the second input data from each element included in the first input data 610 based on the column address to remove the low frequency noise from the third input data. 630 may be generated.

Meanwhile, when the third input data 630 is generated, the second noise removing unit 162 places a zero in the blank area 631 of the third input data 630 generated by the shift of the first input data 610 . (zero) can be inserted.

Specifically, the second noise removing unit 162 may subtract elements disposed at column addresses corresponding to each other from the first input data 610 and the second input data 620 .

The second noise removing unit 162 may store the subtracted element in the third input data 630 . In this case, the second noise removing unit 162 may store the subtracted element at a location of the third input data 630 corresponding to column addresses of the first input data 610 and the second input data 620 . For example, when elements arranged at (1, 1) among the elements included in the first input data 610 and the second input data 620 are subtracted, the second noise removing unit 162 subtracts them. The selected element may be stored at a position (1, 1) of the third input data 630 .

On the other hand, when there is no element of the second input data 620 corresponding to the element selected in the first input data 610 , the second noise removing unit 162 is configured to correspond to the column address of the first input data 610 . A zero may be inserted at the position of the third input data 630 . For example, since there is no second input data corresponding to (1, 9) and (1, 10) of the first input data 610 in FIG. 6 , the second noise removing unit 162 may generate the third input data ( A zero may be inserted at (1, 9) and (1, 10) positions of 630 .

7 is a diagram for explaining an effect generated when a zero is inserted into a blank area of third input data.

Referring to the drawings, in FIG. 7 , when a zero is not inserted into the blank area of the third input data, a first reception signal 711 is generated, and a first cross-correlation signal between the first reception signal 711 and the transmission signal A first detection distance graph 713 using 712 and a first cross-correlation signal 712 is shown. In addition, in FIG. 7 , a second reception signal 714 generated when a zero is inserted in the blank area of the third input data, a second cross-correlation signal 715 between the second reception signal 714 and the transmission signal, and A second detection distance graph 716 using a second cross-correlation signal 715 is shown.

As shown in Fig. 7, it can be seen that the non-operational region 714a of the second reception signal 714 is stabilized by inserting a zero into the blank region of the third input data. Accordingly, the second cross-correlation signal ( It can be seen that the non-operational region 715a of 715 is also stabilized.

As in the first detection distance graph 713 and the second detection distance graph 716 , the first cross-correlation signal 712 is unstable, so that the detection distance fluctuates abruptly between 0 and 80 m, while the second intersection Since the correlation signal 715 is stabilized, the detection distance variation of the second detection distance graph 716 is significantly smaller than the detection distance variation of the first detection distance graph 713 .

8A, 8B, and 9 are diagrams for explaining an effect of increasing a detection distance according to the removal of low-frequency noise of a transmission signal and a reception signal.

In more detail, FIG. 8A shows when the object detection apparatus 100 removes only high-frequency noise from the received signal 812 and then generates a cross-correlation signal 814 between the transmitted signal 811 and the received signal 812 , It is a diagram for explaining the shape of the cross-correlation signal 814 and the influence of noise. Also, FIG. 8B shows a case in which the object detecting apparatus 100 removes high-frequency noise and low-frequency noise from the received signal 816 , and then generates a cross-correlation signal 820 between the transmitted signal 815 and the received signal 817 . , a diagram for explaining the shape of the cross-correlation signal 820 and the influence of noise.

Referring to the drawings, in FIG. 8A , the object detecting apparatus 100 may receive a transmission signal 811 and a reception signal 812 . Since the received signal 812 is a signal reflected from an object, the magnitude of the received signal 812 may be smaller than the magnitude of the transmission signal 811 . Also, the received signal 812 may include noise 712a.

The object detection apparatus 100 may output the received signal 813 from which the high frequency noise has been removed by accumulating the received signal 812 for a preset time and calculating an average value of the accumulated received signal. The received signal 812 may still include a low-frequency noise component.

The object detection apparatus 100 may generate a cross-correlation signal 814 between the transmission signal 811 and the reception signal 813 from which the high frequency noise is removed. The object detection apparatus 100 may calculate a time-of-flight (ToF) of the light based on the peak of the cross-correlation signal 814 , and generate a point cloud based on the time-of-flight of the light.

Meanwhile, as shown in FIG. 8A , when the object detection apparatus 100 removes only the high-frequency noise and then generates the cross-correlation signal 814, the cross-correlation signal 814 includes not only low-frequency noise but also the cross-correlation signal ( Since the sharpness of 814 is low, the object detection apparatus 100 cannot accurately detect a peak in the cross-correlation signal 814 . In addition, the detection of an inaccurate peak results in a sharp change in the detection distance.

On the other hand, since the object detection apparatus 100 of the present disclosure generates a cross-correlation signal after removing high-frequency noise as well as low-frequency noise, there is an effect of improving the detection distance.

Specifically, in FIG. 8B , the object detection apparatus 100 of the present disclosure may receive a transmission signal 815 and a reception signal 816 . The transmission signal 815 of FIG. 8B may correspond to the transmission signal 811 of FIG. 8A , and the reception signal 816 of FIG. 8B may correspond to the reception signal 812 of FIG. 8B .

The object detection apparatus 100 may output the received signal 818 from which the high frequency noise is removed by accumulating the received signal 817 for a preset time and calculating an average value of the accumulated received signal.

In addition, the object detection apparatus 100 element-shifts each of the transmission signal 815 and the reception signal 818 and then subtracts elements corresponding to each other so that the transmission signal 816 from which the low-frequency noise is removed and the low-frequency noise are generated. The removed reception signal 819 may be output.

The object detection apparatus 100 may generate a cross-correlation signal 820 between the low-frequency noise-removed transmission signal 816 and the low-frequency noise-removed reception signal 819 . The object detection apparatus 100 may calculate a time-of-flight (ToF) of light based on the peak of the cross-correlation signal 820 , and generate a point cloud based on the time-of-flight of the light.

As shown in FIG. 8B , it can be seen that most of the noise of the cross-correlation signal 820 has been removed. In addition, since the cross-correlation signal 820 is generated based on the transmission signal 816 from which the low-frequency noise has been removed and the reception signal 819 from which the low-frequency noise has been removed, the cross-correlation signal 820 may have high sharpness. . Accordingly, the object detection apparatus 100 may more accurately detect a peak value from the cross-correlation signal 820 , and accordingly, the detection distance of the object detection apparatus 100 is improved.

9 shows a third detection distance graph 911 when the object detection apparatus 100 generates a cross-correlation signal 911 after only removing high-frequency noise and after the object detection apparatus 100 removes both high-frequency and low-frequency noise. A fourth detection distance graph 912 in the case of generating the cross-correlation signal 913 is shown. 9, the magnitude of the transmission signal is 1V, and the reception signal is accumulated 100 times.

As shown in FIG. 9 , when the object detection apparatus 100 generates the cross-correlation signal 911 after only removing high-frequency noise, an accurate peak position cannot be searched for in the cross-correlation signal 911, so the detection distance is 0 to It fluctuates rapidly at 150 m. On the other hand, when the object detection apparatus 100 generates the cross-correlation signal 913 after removing the high-frequency noise and the low-frequency noise, an accurate peak position can be searched for in the cross-correlation signal 913, so the change in the detection distance is significant. gets smaller

10 is a diagram for explaining a method of calculating the quality of a cross-correlation signal according to an embodiment.

In FIG. 10 , the x-axis represents time, and the y-axis represents voltage or current.

Referring to the drawing, the peak detector 133 may detect a first peak value P1 having the largest absolute value among peak values of the cross-correlation signal S3 . Also, the peak detector 133 may detect the second peak value P2 having the largest absolute value among the remaining peak values excluding the first peak value P1 . The peak detector 133 may output the first peak value P1 and the second peak value P2 to the quality calculator 134 .

The quality calculator 134 may calculate the quality of the cross-correlation signal based on the absolute value of the first peak value P1 and the absolute value of the second peak value P2 .

In an embodiment, the quality calculator 134 may calculate the quality of the cross-correlation signal by using any one of Equations 2 to 5 below.

In Equations 2 to 5, S _QoS may be the quality of the cross-correlation signal, P1 may be a first peak value, and P2 may be a second peak value.

Meanwhile, the point cloud generator 135 may generate a point cloud based on a cross-correlation signal having a preset quality or higher. In other words, the point cloud generator 135 may ignore a cross-correlation signal having a small difference or ratio between the first peak value P1 and the second peak value P2 .

As the point cloud generator 135 generates a point cloud based on a cross-correlation signal having a predetermined reference quality or higher, the possibility of false detection of an object may be remarkably reduced.

11 is a diagram for explaining an effect of preventing false detection according to a quality calculation of a cross-correlation signal.

Referring to the drawings, FIG. 11 shows an original image, a cross-correlation signal having a predetermined quality or higher, and an object image from which noise is removed.

11 , as the quality of the cross-correlation signal is determined and a 3D image is generated based on the determined quality, the object detecting apparatus 100 may acquire the same 3D image as the original.

12 is a flowchart illustrating an object detection method according to an embodiment.

Referring to the drawings, in step S1210 , the object detecting apparatus 100 may receive a transmission signal irradiated toward the object and a reception signal reflected from the object. In this case, the transmission signal may mean a part of the transmission signal transmitted toward the object.

In operation S1220, the object detection apparatus 100 may convert each of the transmission signal and the reception signal into a digital signal according to a preset sampling period.

The object detection apparatus 100 may output the digital signal as vector data in the form of a column vector or a row vector. Vector data may mean an array in the form of a column vector or a row vector consisting of a set of elements. In each element, quantized values of the transmission signal and the reception signal may be stored.

In operation S1230, the object detection apparatus 100 may interpolate between sampling periods.

The object detection apparatus 100 may interpolate between each element included in the vector data by predicting an element between sampling periods. For example, the object detection apparatus 100 may include a linear interpolation method, a polynomial interpolation method, a spline interpolation method, an exponential interpolation method, a log-linear interpolation method, and a log-linear interpolation method. A transmission signal and a reception signal may be interpolated using at least one of a linear interpolation method, a Lagrange interpolation method, a Newton interpolation method, and a two-dimensional interpolation method. . However, the above-described interpolation method is only an example of the interpolation method, and various interpolation methods for interpolating the transmitted signal and the received signal may be used.

In operation S1240 , the object detection apparatus 100 may remove noises of the interpolated transmission signal and the interpolated reception signal.

After removing the high-frequency noise of the interpolated transmission signal and the interpolated reception signal, the object detection apparatus 100 may remove the low-frequency noise of each of the transmission signal from which the high-frequency noise is removed and the reception signal from which the high-frequency noise is removed.

The noise removal method of the object detection apparatus 100 will be described in more detail with reference to FIGS. 14 to 15 .

In operation S1250 , the object detection apparatus 100 may generate a cross-correlation signal between a noise-removed transmission signal and a noise-removed reception signal.

The object detection apparatus 100 may generate a cross-correlation signal between a noise-removed transmission signal and a noise-removed reception signal using Equation 1, but is not limited thereto.

In operation S1260 , the object detection apparatus 100 may acquire a 3D image of the object based on the peak value of the cross-correlation signal.

13 is a flowchart for explaining the method of removing high-frequency noise of FIG. 12 .

Referring to the drawing, in operation S1310, the object detection apparatus 100 may accumulate each element value included in the interpolated vector data for a preset time.

In operation S1320 , the object detection apparatus 100 may remove the high-frequency noise by outputting an average value of the accumulated elements.

According to an embodiment, each step of FIG. 13 may be performed only for a received signal.

14 is a flowchart for explaining the low-frequency noise removal method of FIG. 12 .

Referring to the drawings, in operation S1410 , the object detection apparatus 100 may receive vector data from which high frequency noise is removed as first input data.

In operation S1420 , the object detecting apparatus 100 may generate second input data by shifting each element included in the first input data by a preset direction and a preset size.

The preset direction may be any one of left, right, upper, and lower directions. When the vector data is a row vector, the preset direction may be set to the left or the right. In this case, the left side may mean a direction in which the column address of the vector data decreases, and the right side may indicate a direction in which the column address of the vector data increases. Also, when the vector data is a column vector, the preset direction may be set to the upper side or the lower side. In this case, the upper side may mean a direction in which the row address of the vector data decreases, and the lower side may indicate a direction in which the row address of the vector data increases. The preset size may be set to 500 elements.

When shifting an element, the object detecting apparatus 100 may delete elements out of a column address range. Accordingly, the length of the second input data may be shorter than the length of the first input data.

In operation S1430 , the object detection apparatus 100 may output third input data from which low-frequency noise is removed by subtracting each element included in the second input data from each element included in the first input data.

The object detection apparatus 100 may subtract elements disposed at column addresses corresponding to each other from the first input data and the second input data.

The object detection apparatus 100 may store the subtracted element in the third input data. In this case, the object detection apparatus 100 may store the subtracted element at positions of the third input data corresponding to column addresses of the first input data and the second input data.

On the other hand, when there is no element of the second input data corresponding to the element selected in the first input data, the object detection apparatus 100 sets the position of the third input data corresponding to the column address of the first input data to zero. can be inserted.

15 is a flowchart illustrating the 3D image acquisition method of FIG. 12 .

Referring to the drawing, in operation S1510, the object detection apparatus 100 may detect at least one peak value from the cross-correlation signal.

The object detection apparatus 100 may detect a first peak value having the largest absolute value among peak values of the cross-correlation signal. Also, the object detection apparatus 100 may detect a second peak value having the largest absolute value among the remaining peak values except for the first peak value.

In operation S1520, the object detection apparatus 100 may determine the quality of the cross-correlation signal based on the peak value.

The object detection apparatus 100 may determine the quality of the cross-correlation signal based on the absolute value of the first peak value and the absolute value of the second peak value. The object detection apparatus 100 may determine the quality of the cross-correlation signal according to Equations 2 to 5.

In operation S1530 , the object detection apparatus 100 may generate a point cloud based on a cross-correlation signal having a quality greater than or equal to a preset quality.

The object detection apparatus 100 may calculate the transmission time of the transmission signal and the reception time of the reception signal based on the first peak value of the cross-correlation signal of the reference quality or higher. Also, the object detection apparatus 100 may calculate the flight time of the light output from the transmitter 110 based on the transmission time and the reception time. Also, the object detecting apparatus 100 may calculate a distance to the object based on the flight time of the light. Also, the object detection apparatus 100 may generate a three-dimensional point cloud based on distance information to the object.

Meanwhile, the object detection apparatus 100 may ignore the peak value of the cross-correlation signal having a lower quality than the reference quality. Also, the object detection apparatus 100 may map the maximum detection distance information to a point cloud corresponding to a cross-correlation signal of less than a reference quality.

In operation S1540, the object detection apparatus 100 may acquire a 3D image based on the generated point cloud.

Meanwhile, the above-described embodiments can be written as a program that can be executed on a computer, and can be implemented in a general-purpose digital computer that operates the program using a computer-readable recording medium. In addition, the structure of data used in the above-described embodiments may be recorded in a computer-readable recording medium through various means. The computer-readable recording medium includes a storage medium such as a magnetic storage medium (eg, a ROM, a floppy disk, a hard disk, etc.) and an optically readable medium (eg, a CD-ROM, a DVD, etc.).

Those of ordinary skill in the art related to the present embodiment will understand that the embodiment may be implemented in a modified form without departing from the essential characteristics of the above description. Therefore, the disclosed embodiments are to be considered in an illustrative rather than a restrictive sense. The scope of the rights is indicated in the claims rather than the above description, and all differences within the scope equivalent thereto should be construed as included in the present embodiment.

100: object detection device
110: transmitter
120: receiver
130: control unit
132: cross-correlation part
133: peak detection unit
134: quality calculator
135: point cloud generator
140: conversion unit
150: interpolation unit
160: filter unit

Claims (15)

In the object detection apparatus for irradiating a transmission signal toward an object and receiving a received signal reflected from the object,
a converter converting each of the transmission signal and the reception signal into a digital signal according to a preset sampling period;
an interpolation unit for interpolating between the sampling periods;
a filter unit for removing noise of the interpolated transmission signal and the interpolated reception signal; and
A controller for generating a cross correlation signal between the noise-removed transmission signal and the noise-removed reception signal, and obtaining a three-dimensional image of the object based on a peak value of the cross-correlation signal ; object detection device including. According to claim 1,
the conversion unit
The object detection apparatus converts each of the transmission signal and the reception signal into vector data in a column vector or row vector format and outputs the converted vector data. 3. The method of claim 2,
The interpolation unit
An object detection apparatus for interpolating between each element included in the vector data. According to claim 1,
the filter unit
and a first noise removing unit for accumulating each element included in the interpolated vector data for a preset time and outputting an average value of the accumulated elements to remove high-frequency noise. 5. The method of claim 4,
the filter unit
receiving the vector data from which the high-frequency noise has been removed as first input data;
generating second input data by shifting each element included in the first input data by a preset direction and a preset size;
and a second noise remover configured to output third input data from which low-frequency noise is removed by subtracting each element included in the second input data from each element included in the first input data. 6. The method of claim 5,
The second noise removing unit
When there is no element of the second input data corresponding to the element of the first input data, a zero is inserted into the third input data. According to claim 1,
the control unit
detecting at least one peak value in the cross-correlation signal;
determining the quality of the cross-correlation signal based on the peak value,
An object detecting apparatus for obtaining a three-dimensional image of the object based on the quality of the cross-correlation signal. 8. The method of claim 7,
the control unit
detecting a first peak value having the largest absolute value among the peak values of the cross-correlation signal;
detecting a second peak value having the largest absolute value among the remaining peak values except for the first peak value;
The object detection apparatus is configured to determine the quality of the cross-correlation signal based on the absolute value of the first peak value and the absolute value of the second peak value. 9. The method of claim 8,
the control unit
generating a point cloud based on the cross-correlation signal equal to or greater than a preset reference quality;
An object detection apparatus for obtaining a three-dimensional image of the object based on the generated point cloud. In the object detection method,
Receiving the transmitted signal irradiated toward the object and the received signal reflected from the object;
converting each of the transmission signal and the reception signal into a digital signal according to a preset sampling period;
interpolating between the sampling periods;
removing noise from each of the interpolated transmission signal and the interpolated reception signal;
generating a cross-correlation signal between the noise-removed transmission signal and the noise-removed reception signal; and
and obtaining a three-dimensional image of the object based on the peak value of the cross-correlation signal. 11. The method of claim 10,
The converting step is
converting each of the transmission signal and the reception signal into vector data in the form of a column vector or a row vector and outputting,
The interpolation step is
and interpolating between each element included in the vector data. 11. The method of claim 10,
The removing step
removing high-frequency noise by accumulating each element included in the interpolated vector data for a preset time and outputting an average value of the accumulated elements;
receiving the vector data from which the high frequency noise has been removed as first input data;
generating second input data by shifting each element included in the first input data by a preset direction and a preset size;
and outputting third input data from which low-frequency noise is removed by subtracting each element included in the second input data from each element included in the first input data. 13. The method of claim 12,
The step of outputting the third input data is
and inserting a zero into third input data when there is no element of the second input data corresponding to the element of the first input data. 11. The method of claim 10,
The obtaining step is
detecting at least one peak value in the cross-correlation signal;
determining a quality of the cross-correlation signal based on the peak value; and
and obtaining a three-dimensional image of the object based on the quality of the cross-correlation signal. 15. The method of claim 14,
The detecting step
detecting a first peak value having the largest absolute value among the peak values of the cross-correlation signal; and
detecting a second peak value having the largest absolute value among the remaining peak values except for the first peak value;
The judging step
determining the quality of the cross-correlation signal based on the absolute value of the first peak value and the absolute value of the second peak value;
The obtaining step is
generating a point cloud based on the cross-correlation signal of a preset reference quality or higher; and
and obtaining a three-dimensional image of the object based on the generated point cloud.

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