CN112034423B - High-precision mobile vehicle positioning method based on LED visible light communication - Google Patents
High-precision mobile vehicle positioning method based on LED visible light communication Download PDFInfo
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Abstract
The invention discloses a high-precision mobile vehicle positioning method based on LED visible light communication by utilizing an LED street lamp and a camera image sensor on a mobile vehicle. The LED street lamps on two sides of the road send a modulation signal containing the position information of the LED street lamps, such as an OOK or Manchester signal. Through free space transmission, the receiving end is a camera installed in a mobile vehicle and receives in a rolling shutter working mode, and the data of the receiving end is an image sequence containing a plurality of LED street lamps. And (3) positioning the LED signal sources in the continuous frame images by adopting a digital image processing algorithm to obtain the image of the target LED street lamp. And recovering the modulation signal sent by the target LED street lamp by adopting a digital signal processing method. In addition, based on a geometric ranging algorithm of small hole imaging, the transverse distance and the longitudinal distance of the mobile vehicle relative to the target LED street lamp are calculated, and the high-precision positioning of the mobile vehicle is realized by combining the modulation signals sent by the recovered target LED street lamp. The method provided by the invention adopts the camera image sensor to receive, has spatial separability, can effectively eliminate the interference of noise light sources, has low cost and simple realization, and can realize the high-precision positioning of the mobile vehicle in the daytime and at night.
Description
Field of the art
The invention belongs to a mobile vehicle positioning method based on LED Visible Light Communication in a Visible Light Communication (VLC) system.
(II) background art
Intelligent Transportation Systems (ITS) reduce traffic accidents and related casualties by using advanced communication technologies. In addition, the ITS provides real-time access to related traffic information, and traffic is effectively monitored and managed, so that congestion can be reduced and an optimized alternative route can be provided according to traffic conditions, and the efficiency of a traffic system is improved. Vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-cloud (V2C), vehicle-to-sensor (V2S), and vehicle-to-personal device (V2P) are critical parts of ITS for all (V2X) communication systems, playing an important role in reducing road traffic accidents and improving traffic efficiency. Visible Light Communication (VLC), which is a communication mechanism, has advantages of wide bandwidth, electromagnetic interference resistance, and easy application, as compared with Radio Frequency (RF) communication, and has been attracting attention in research of ITS. VLC includes Light Emitting Diodes (LEDs) for transmitting data and Photodiodes (PDs) or Image Sensors (IS) for receiving LED information. VLC uses the visible spectrum, and its line of sight (LOS) transmission requirements ensure the security of information and the absence of multipath or electromagnetic interference from RF communications. If the image sensor is adopted as a receiving end, the image sensor has spatial separability, so that different LED signal sources can be distinguished, and meanwhile, the interference of environmental noise can be eliminated.
Accurate vehicle positioning is an integral part of intelligent transportation systems, and is critical to providing safety measures and autonomous navigation. Currently, the most common positioning technology is the Global Positioning System (GPS), and GPS signals are not accurate and reliable due to the influence of high-rise building blocks, and in addition, when a vehicle is in the ground or in a tunnel, there is a shortage of reliability in adopting GPS positioning. For intelligent traffic systems, besides GPS, a laser detection and measurement (LiDAR) system and a radio detection and ranging (RADAR) system based on a sensor are two feasible technologies in vehicle positioning, and have the characteristics of high positioning accuracy, low delay and the like, however, the two systems require expensive and complex equipment, and are difficult to be widely applied. In recent years, as an emerging technology, LED-based visible light communication can provide communication and illumination at the same time, and in addition, can be used to provide positioning services. The LED tail or head lights of a vehicle are used to transmit a modulated signal that is received by two photodiodes mounted in another vehicle, and the relative position between the two vehicles can be determined using a time difference of arrival (TDOA) algorithm. However, in the TDOA algorithm, a small error in time measurement causes a large positioning error, and thus, it is difficult to realize high-precision positioning in practice. In addition, the position of the vehicle can be determined by using a Received Signal Strength (RSS) algorithm, and there is a problem in that the positioning accuracy is not high. Since photodiodes cannot distinguish between different light sources, these systems are susceptible to ambient light, especially sunlight.
Aiming at the problems, the invention provides a high-precision mobile vehicle positioning method based on LED visible light communication. The transmitting end is an LED street lamp at two sides of a road, the LED street lamp transmits a modulation signal containing the position information of the LED street lamp, such as an OOK or Manchester signal, and the receiving end is a camera installed in a mobile vehicle through free space transmission. The method comprises the steps that a camera image sensor in a vehicle is used for receiving modulation signals sent by LED street lamps at two sides of a road, the data of a receiving end are image sequences comprising a plurality of LED street lamps, a digital image processing algorithm is used for obtaining position coordinates of the LED street lamps in an image, and two LED street lamp images closest to the vehicle are used as images of target LED street lamps. At the decoding end, a digital signal processing method is adopted for the image of the target LED street lamp, and the modulating signal which is sent by the target LED street lamp and contains the position information of the target LED street lamp is recovered. In addition, based on a geometric ranging algorithm of small hole imaging, the geometric relationship between a world coordinate system and an image coordinate system is utilized to calculate the transverse distance and the longitudinal distance of the mobile vehicle relative to the LED street lamp, and the mobile vehicle is positioned by combining the restored modulating signals of which the target LED street lamp contains the position information of the target LED street lamp. Because the receiving end adopts the camera image sensor with space separability, different light sources can be separated, the influence of noise light sources is eliminated, and the signal processing process of the decoding end is simplified. In addition, by setting the shutter speed and sensitivity of the camera image sensor, the influence of ambient light can be eliminated in both the daytime and the night. The high-precision mobile vehicle positioning method based on LED visible light communication is low in cost, simple to implement and has innovative practical value.
(III) summary of the invention
The high-precision mobile vehicle positioning method based on LED visible light communication is low in cost, simple to realize and capable of realizing high-precision positioning of the mobile vehicle.
In order to achieve the above object, the high-precision mobile vehicle positioning method based on LED visible light communication adopted by the invention comprises the following steps:
step 1: the LED street lamp is arranged at the two sides of the road, and the LED street lamp transmits a modulation signal containing the position information of the LED street lamp, wherein the modulation signal is an OOK or Manchester signal;
step 2: the receiving end is a camera installed in the mobile vehicle and receives the data by adopting a working mode of a rolling shutter through free space transmission, and the data of the receiving end is an image sequence comprising a plurality of LED street lamps;
step 3: at a receiving end, a digital image processing algorithm is adopted, background noise existing in images is eliminated, positioning of LED signal sources in continuous frame images is achieved, position coordinates of LED street lamps in the images are obtained, and two LED street lamp images closest to a vehicle are taken as images of target LED street lamps;
step 4: at the decoding end, a digital signal processing method is adopted to recover the modulation signal which is sent by the target LED street lamp and contains the self position information, and a sampling frequency deviation dynamic compensation algorithm is provided for solving the problem of sampling frequency deviation caused by inaccurate clock recovery of the receiving end, so that the influence of the sampling frequency deviation on the communication performance is reduced;
step 5: based on a geometric ranging algorithm of small hole imaging, the transverse distance and the longitudinal distance between the mobile vehicle and the target LED street lamp are calculated, and the high-precision positioning of the mobile vehicle is realized by combining the restored modulating signals of the target LED street lamp containing the position information of the mobile vehicle.
(IV) description of the drawings
FIG. 1 is a schematic diagram of a high-precision mobile vehicle positioning method based on LED visible light communication of the present invention;
FIG. 2 is a flow chart of the invention for obtaining a target LED street lamp image using a digital image processing algorithm;
FIG. 3 is a flow chart of recovering a modulated signal at a decoding end of visible light communication according to the present invention;
FIG. 4 is a flow chart of the sampling frequency deviation dynamic compensation algorithm of the present invention;
FIG. 5 is a scene graph of a geometric ranging algorithm based on aperture imaging according to the present invention;
FIG. 6 is a flow chart of a geometric ranging algorithm based on aperture imaging of the present invention;
FIG. 7 is a flow chart of the present invention for achieving high accuracy positioning of a moving vehicle;
(fifth) detailed description of the invention
The present invention will be specifically described with reference to the following experimental examples and drawings.
Fig. 1 shows a high-precision mobile vehicle positioning method based on LED visible light communication. The transmitting end is an LED street lamp at two sides of the road, the LED street lamp transmits a modulation signal containing the position information of the LED street lamp, and the modulation signal is an OOK or Manchester signal. Through free space transmission, the receiving end is a camera placed in the mobile vehicle, and the camera receives in a working mode of the rolling shutter. And (3) for a continuous image sequence containing a plurality of LED street lamps received by the camera image sensor, eliminating noise existing in an image background by adopting a digital image processing algorithm, determining the position coordinates of the LED street lamps in the image, and taking two LED street lamp images closest to a vehicle as images of a target LED street lamp. And then, at the visible light communication decoding end, recovering the modulating signal which is sent by the target LED street lamp and contains the position of the target LED street lamp by adopting a digital signal processing method. And then, calculating the transverse distance and the longitudinal distance between the moving vehicle and the target LED street lamp based on a geometric ranging algorithm of the pinhole imaging. And finally, combining the restored target LED street lamp with the modulating signal containing the position information of the target LED street lamp to realize the high-precision positioning of the mobile vehicle.
Fig. 2 is a flowchart of the method for obtaining the image of the target LED street lamp by using the digital image processing algorithm. For continuous images which are received by a camera image sensor and contain a plurality of LED street lamps, firstly, graying and binarizing the continuous images, and then, adopting morphological open operation to eliminate environmental noise existing in an image background; secondly, performing morphological closing operation and contour extraction on the image with the background noise removed to obtain the approximate contour of the LED street lamp in the image, and solving the minimum external rectangle of the approximate contour to obtain the accurate contour of the LED street lamp; next, the barycenter point coordinates of the accurate outline are obtained, the LED signal sources in the image are positioned, and the position coordinates of the LED street lamp in the image are determined; and finally, outputting two LED street lamp images farthest from the middle row of the image, namely, two LED street lamp images closest to the vehicle as images of the target LED street lamp, so as to realize accurate positioning.
Fig. 3 is a flowchart of the visible light communication decoding end of the present invention for recovering the modulated signal. At the receiving end, the camera works in a rolling shutter mode, namely, the camera is exposed line by line from top to bottom, so that the modulation signals sent by the LED street lamps are presented in black and white stripes with different widths in images received by the camera. For the image received by the camera, according to the image of the target LED street lamp, firstly, graying the image; secondly, acquiring a pixel gray value sequence of a middle column of a target LED street lamp in an image, and filtering the gray value sequence by adopting a digital low-pass filter to eliminate the influence of noise; then, performing threshold judgment on the gray value sequence by using third-order fitting operation, wherein the judgment that the gray value is higher than the threshold value is bit 1, and the judgment that the gray value is lower than the threshold value is bit 0, so that a binary data sequence is obtained; then, the binary data sequence is sampled, in order to reduce the influence of sampling frequency deviation on communication performance caused by inaccurate clock recovery of a receiving end, a sampling frequency deviation dynamic compensation algorithm is provided, and bit error rate performance is effectively improved; and finally, recovering the modulating signal which is sent by the target LED street lamp and contains the self position information. Fig. 4 is a flowchart of the sampling frequency deviation dynamic compensation algorithm of the present invention. Firstly, inputting a threshold value judgment to obtain a binary data sequence; then, determining sampling interval SI according to frame head size, calculating sequence S of each small segment with continuous 1 or 0 i Length L of (2) i I.e. the number of bits of this small segment; then, a sequence S with continuous '1' or '0' appearing in each small segment is calculated according to the formula (1) i N of the actual number of bits of (a) i The method comprises the steps of carrying out a first treatment on the surface of the Finally, sampling is carried out, and the sent light of the target LED street lamp is recoveredIs a binary data of (a) in a memory.
Fig. 5 is a scene graph of the geometric ranging algorithm based on pinhole imaging of the present invention.
Fig. 6 is a flow chart of the geometric ranging algorithm based on pinhole imaging of the present invention. First, the world coordinate of the center of the left-hand target LED street lamp on the road is (X) l ,Y l ,Z l ) Which corresponds to a coordinate (x) l ,y l ) The method comprises the steps of carrying out a first treatment on the surface of the The world coordinate of the center of the target LED street lamp on the right side of the road is (X) r ,Y r ,Z r ) Which corresponds to a coordinate (x) r ,y r ) The method comprises the steps of carrying out a first treatment on the surface of the The coordinates of the center pixel point of the acquired image are (x mid ,y mid ) The method comprises the steps of carrying out a first treatment on the surface of the The longitudinal distance between the camera in the vehicle and the two target LED street lamps is D, and the transverse distance between the camera in the vehicle and the left target LED street lamp is S l The transverse distance between the LED street lamp and the right target LED street lamp is S r The method comprises the steps of carrying out a first treatment on the surface of the Then, because the heights of the left and right target LED street lamps are the same and are only different by a fixed distance in the Y-axis direction, the distance is marked as L; meanwhile, the internal parameter focal length of the camera is f. The following formula can be defined by the above definition:
Z l ＝Z r (2)
X l ＝X r (3)
L＝|Y l -Y r | (4)
where || represents taking absolute value notation.
The distance D, S can be obtained by combining the principle of aperture imaging with the principle of triangle similarity l ，S r Is calculated according to the formula:
wherein l is the physical distance between the center points of the left and right target LED street lamps on the image, and the calculation formula is as follows:
l＝|dy×(y l -y r )| (8)
where dy is the actual physical distance between pixel points in the horizontal direction on the image sensor plane in the camera. Therefore, by combining the calculation formulas (5), (6) and (7) with the calculation formula (8) of the distance l, the longitudinal distance D between the vehicle and the target LED street lamp and the transverse distance S between the vehicle and the left target LED street lamp can be calculated l Lateral distance S to right target LED street lamp r . Fig. 7 is a flowchart showing the implementation of the high-precision positioning of a moving vehicle according to the present invention. For a particular location of the moving vehicle on the road, i.e. a particular value of the X, Y axis coordinates. First, inputting the distance D, S calculated by the geometric ranging algorithm based on aperture imaging l ，S r And decoding and recovering the modulation signals of the position information of the target LED street lamps at the two sides of the road through the visible light communication receiving end. When the world coordinate of the center of the target LED street lamp on the left side of the road is (X) l ,Y l ,Z l ) The world coordinate of the center of the right-side target LED street lamp of the road is (X) r ,Y r ,Z r ) As for the X-coordinate of the vehicle, it can be seen from the scene graph in fig. 5:
X＝X l -D＝X r -D (9)
for the Y coordinate of the vehicle, it can be seen from the scene graph in fig. 5:
Y＝S l +Y l ＝Y r -S r (10)
and finally integrating the X and Y coordinates and outputting the world coordinates (X and Y) of the vehicle.
The implementation steps are as follows:
step 1: the LED street lamp is arranged at the two sides of the road, and the LED street lamp transmits a modulation signal containing the position information of the LED street lamp, wherein the modulation signal is an OOK or Manchester signal;
step 2: the receiving end is a camera arranged in the mobile vehicle after free space transmission, the camera receives in a working mode of a rolling shutter, and data of the receiving end is an image sequence containing a plurality of LED street lamps;
step 3: at the receiving end, the received image comprises a plurality of far-to-near LED street lamps, an image processing method is adopted to eliminate environmental noise existing in the image background, the positioning of LED signal sources in continuous frame images is realized, the position coordinates of the LED street lamps in the images are obtained, as shown in fig. 2, the received image is firstly subjected to graying and binarization, and then morphological opening operation is adopted to eliminate the background noise in the image; then, the image after noise elimination is subjected to morphological closing operation, contour extraction and minimum circumscribed rectangle calculation to obtain the accurate contour of the LED street lamp in the image; and finally, extracting the centroid point of the LED street lamp in the image, and selecting two LED street lamps farthest from the middle line of the image, namely, the images of the two LED street lamps closest to the moving vehicle as the images of the target LED street lamps so as to realize accurate positioning of the vehicle.
Step 4: at the decoding end, as shown in fig. 3, an image of a target LED street lamp is input, and first, a pixel gray value sequence in the middle of the target LED street lamp image is extracted from the target LED street lamp image; then, a digital low-pass filter is adopted to eliminate the influence of noise; then, threshold judgment is carried out on the filtered gray value sequence by adopting third-order fitting to obtain a binary data sequence; and finally, sampling the binary data sequence to recover the modulation signal sent by the target LED street lamp.
Step 5: in order to reduce the influence of sampling frequency deviation on visible light communication performance caused by inaccurate clock recovery of a receiving end, a sampling frequency deviation dynamic compensation algorithm is provided, as shown in fig. 4, a binary data sequence obtained after threshold judgment is dynamically compensated during sampling, a dynamic range is set for the pixel line number actually represented by each data bit, the defect of fixed interval sampling in the traditional scheme is effectively overcome, and the bit error rate performance is improved.
Step 6: based on the graph6, according to the geometric ranging algorithm flow chart of the small hole imaging, the world coordinate of the center of the target LED street lamp on the left side of the road is (X) l ,Y l ,Z l ) The coordinates on the image are (x l ,y l ) The method comprises the steps of carrying out a first treatment on the surface of the The world coordinate of the center of the target LED street lamp on the right side of the road is (X) r ,Y r ,Z r ) The coordinates on the image are (x r ,y r ) The method comprises the steps of carrying out a first treatment on the surface of the The coordinates of the center pixel point of the acquired image are (x mid ,y mid ) The method comprises the steps of carrying out a first treatment on the surface of the The heights of the left and right target LED street lamps are the same and differ by a fixed distance only in the Y-axis direction, and the distance is marked as L; the internal parameter focal length of the camera is f; l is the physical distance between the center points of the left and right target LED street lamps on the acquired image; the longitudinal distance D between the vehicle and the target LED street lamp and the transverse distance S between the vehicle and the left target LED street lamp are calculated by combining the principle of aperture imaging with the principle of triangle similarity and corresponding formulas l Lateral distance S to right target LED street lamp r 。
Step 7: as shown in fig. 7, distances D, S calculated by a geometric ranging algorithm based on aperture imaging are input l ，S r Decoding and recovering the modulation signals containing the position information of the two-side target LED street lamp of the road through the visible light communication receiving end, and according to the distances D and S l ，S r And calculating world coordinates (X, Y) of the vehicle according to the corresponding relation between the LED street lamp position information and the target LED street lamp at the two sides of the road, and realizing high-precision positioning of the moving vehicle.
(six) major technical advantages
According to the invention, for the mobile vehicle, based on visible light communication, the camera arranged in the mobile vehicle is adopted to receive the modulation signals containing the self-position information and sent by the LED street lamps at the two sides of the road, so that the mobile vehicle is positioned with high precision. The LED street lamp is characterized in that the sending end is an LED street lamp on two sides of a road, the LED street lamp sends a modulation signal containing self position information, such as OOK or Manchester signals, the LED street lamp is transmitted in free space, the receiving end is a camera arranged in a mobile vehicle, the camera receives in a rolling shutter working mode, and data of the receiving end are image sequences containing a plurality of LED street lamps. And (3) positioning the LED signal sources in the continuous frame images by adopting an image processing algorithm, obtaining the positions of the LED street lamps in the images, and taking two LED street lamp images closest to the vehicle as the images of the target LED street lamps. And at the visible light communication decoding end, recovering the OOK or Manchester signals containing the self position information and sent by the target LED street lamp by adopting a digital signal processing method. Based on a geometric ranging algorithm of small hole imaging, the transverse and longitudinal distances between the mobile vehicle and the target LED street lamp are calculated, and the high-precision positioning of the mobile vehicle is realized by combining the restored modulating signals of the target LED street lamp containing the position information of the mobile vehicle.
The high-precision mobile vehicle positioning method based on LED visible light communication has the advantages that the receiving end adopts the camera image sensor with space separability, so that the interference of a noise light source can be effectively eliminated, the signal processing process of the visible light communication decoding end is simplified, the cost is low, the realization is simple, the high-precision mobile vehicle positioning can be realized in the daytime and at night, and the high-precision mobile vehicle positioning method based on LED visible light communication has practical value.
Claims (3)
1. The high-precision mobile vehicle positioning method based on LED visible light communication is characterized by comprising the following steps of:
the transmitting end is an LED street lamp at two sides of the road, and the LED street lamp transmits a modulation signal containing the position information of the LED street lamp; the modulation signal sent by the LED street lamp is an OOK or Manchester signal;
the receiving end is a camera installed in the mobile vehicle after free space transmission, and the camera at the receiving end works in a rolling shutter mode; the data of the receiving end is an image sequence containing a plurality of LED street lamps;
the receiving end adopts a digital image processing algorithm, which comprises image graying, binarization, morphological open operation, morphological close operation, contour extraction, minimum circumscribed rectangle calculation, centroid extraction and coordinate pairing of LEDs in the image; for continuous images containing a plurality of LED street lamps received by a camera image sensor, firstly, carrying out graying and binarization on the continuous images, then adopting morphological open operation to eliminate environmental noise in an image background, secondly, carrying out morphological closed operation and contour extraction on the image after eliminating the background noise to obtain the rough contour of the LED street lamps in the image, then obtaining the minimum circumscribed rectangle of the rough contour to obtain the accurate contour of the LED street lamps, and then obtaining the centroid point coordinates of the accurate contour to realize the positioning of LED signal sources in continuous frame images, obtain the position coordinates of the LED street lamps in the images, and taking two LED street lamp images closest to a vehicle as the images of a target LED street lamp;
the decoding end adopts a digital signal processing method, which comprises the steps of obtaining a gray value sampling sequence, adopting a low-pass filter to eliminate current noise, and adopting a threshold value judgment and sampling frequency deviation dynamic compensation algorithm; at a receiving end, for an image received by a camera, according to the image of a target LED street lamp, firstly, graying the image, secondly, obtaining a pixel gray value sequence of a middle column of the target LED street lamp in the image, filtering the gray value sequence by adopting a digital low-pass filter to eliminate the influence of noise, then, carrying out threshold judgment on the gray value sequence by using a third-order fitting operation, judging that the gray value is higher than the threshold and is bit 1, and judging that the gray value is lower than the threshold and is bit 0, thus obtaining a binary data sequence, then, sampling the binary data sequence, and adopting a sampling frequency deviation dynamic compensation algorithm to effectively improve the bit error rate performance in order to reduce the influence of sampling frequency deviation on communication performance caused by inaccurate clock recovery of the receiving end, and finally, recovering a modulation signal which is sent by the target LED street lamp and contains self position information;
and calculating the transverse distance and the longitudinal distance between the mobile vehicle and the target LED street lamp by adopting a geometric ranging algorithm based on small-hole imaging, and combining the restored modulation signals of the target LED street lamp containing the position information of the mobile vehicle to realize high-precision positioning of the mobile vehicle.
2. The method for locating a mobile vehicle with high accuracy based on LED visible light communication according to claim 1, wherein said sampling frequency deviation dynamic compensation algorithm is characterized in that firstly, a binary data sequence is obtained after inputting a threshold decision, then, a sampling interval SI is determined according to the frame head size, and each small is calculatedThe segments present a sequence S of consecutive "1" or "0 i Length L of (2) i I.e. the number of bits of the segment, and then a sequence S of successive "1" or "0" occurrences of each segment is calculated according to equation (1) i N of the actual number of bits of (a) i And finally, sampling is carried out, and binary data sent by the target LED street lamp is recovered.
3. The method for positioning a mobile vehicle with high accuracy based on LED visible light communication according to claim 1, wherein the geometric ranging algorithm based on pinhole imaging is characterized in that, first, the world coordinate of the center of the left target LED street lamp on the road is (X 1 ，Y 1 ，Z 1 ) Which corresponds to a coordinate (x) 1 ，y 1 ) The world coordinate of the center of the right-side target LED street lamp of the road is (X) r ，Y r ，Z r ) Which corresponds to a coordinate (x) r ，y r ) The coordinates of the center pixel point of the acquired image are (x mid ，y mid ) The longitudinal distance between the camera in the vehicle and the two target LED street lamps is D, and the transverse distance between the camera in the vehicle and the left target LED street lamp is S 1 The transverse distance between the LED street lamp and the right target LED street lamp is S r Then, because the heights of the left and right target LED street lamps are the same and only differ by a fixed distance in the Y-axis direction, the distance is marked as L, and meanwhile, the focal length of the internal parameters of the camera is f, the following formula can be obtained by the definition;
Z l ＝Z r (2)
X l ＝X r (3)
L＝|Y l -Y r | (4)
wherein, I.S represents taking absolute value sign, and the distance D, S can be obtained by combining the principle of aperture imaging with the principle of triangle similarity 1 ，S r Is calculated according to the formula:
wherein l is the physical distance between the center points of the left and right target LED street lamps on the image, and the calculation formula is as follows:
l＝|dy×(y l -y r )| (8)
wherein dy is the actual physical distance between the pixels in the horizontal direction on the plane of the image sensor in the camera, so the longitudinal distance D between the vehicle and the target LED street lamp and the transverse distance S between the vehicle and the left target LED street lamp can be calculated by combining the calculation formulas (5), (6), (7) and the calculation formula (8) of the distance l 1 Lateral distance S to right target LED street lamp r For a specific position of a moving vehicle on a road, namely, a specific numerical value of X, Y-axis coordinates, firstly, inputting distances D, S calculated by a geometric ranging algorithm based on aperture imaging 1 ，S r And decoding the recovered modulated signal containing the position information of the target LED street lamp at the two sides of the road by the visible light communication receiving end, wherein when the world coordinate of the center of the target LED street lamp at the left side of the road is (X) 1 ，Y 1 ，Z 1 ) The world coordinate of the center of the right-side target LED street lamp of the road is (X) r ，Y r ，Z r ) As for the X coordinate of the vehicle, it is known that:
X＝x l -D＝X r -D (9)
as for the Y coordinate of the vehicle, it is known that:
Y＝S l +Y l ＝Y r -S r (10)
and finally integrating the X and Y coordinates and outputting the world coordinates (X and Y) of the vehicle.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105303153A (en) * | 2014-07-23 | 2016-02-03 | 中兴通讯股份有限公司 | Vehicle license plate identification method and apparatus |
| CN105678787A (en) * | 2016-02-03 | 2016-06-15 | 西南交通大学 | Heavy-duty lorry driving barrier detection and tracking method based on binocular fisheye camera |
| CN107622295A (en) * | 2017-09-20 | 2018-01-23 | 华南理工大学 | It is a kind of based on LED flat lamp the barcode encoding coding/decoding methods of EAN 13 and system |
| CN107864013A (en) * | 2017-11-10 | 2018-03-30 | 深圳市光域物联科技有限公司 | Towards the self adaptive imaging Position Fixing Navigation System and method of automatic driving vehicle |
| CN109345015A (en) * | 2018-09-30 | 2019-02-15 | 百度在线网络技术（北京）有限公司 | Method and apparatus for choosing route |
| CN109935100A (en) * | 2017-12-18 | 2019-06-25 | 福特全球技术公司 | To the vehicle monitoring of infrastructure illumination |
| KR101971370B1 (en) * | 2017-12-18 | 2019-08-13 | 국민대학교산학협력단 | Method and apparatus for estimating location of vehicle using optical camera communication |
| CN110852250A (en) * | 2019-11-07 | 2020-02-28 | 厦门市美亚柏科信息股份有限公司 | Vehicle weight removing method and device based on maximum area method and storage medium |
| CN111025365A (en) * | 2019-12-24 | 2020-04-17 | 东南大学 | Method for assisting in high-precision positioning of vehicle by two adjacent street lamps |
| CN111505577A (en) * | 2020-04-27 | 2020-08-07 | 湖南大学 | Mobile vehicle positioning method based on visible light communication |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130057158A1 (en) * | 2010-03-01 | 2013-03-07 | Led Roadway Lighting Ltd. | Gps-based streetlight wireless command and control system |
-
2020
- 2020-09-08 CN CN202010933679.5A patent/CN112034423B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105303153A (en) * | 2014-07-23 | 2016-02-03 | 中兴通讯股份有限公司 | Vehicle license plate identification method and apparatus |
| CN105678787A (en) * | 2016-02-03 | 2016-06-15 | 西南交通大学 | Heavy-duty lorry driving barrier detection and tracking method based on binocular fisheye camera |
| CN107622295A (en) * | 2017-09-20 | 2018-01-23 | 华南理工大学 | It is a kind of based on LED flat lamp the barcode encoding coding/decoding methods of EAN 13 and system |
| CN107864013A (en) * | 2017-11-10 | 2018-03-30 | 深圳市光域物联科技有限公司 | Towards the self adaptive imaging Position Fixing Navigation System and method of automatic driving vehicle |
| CN109935100A (en) * | 2017-12-18 | 2019-06-25 | 福特全球技术公司 | To the vehicle monitoring of infrastructure illumination |
| KR101971370B1 (en) * | 2017-12-18 | 2019-08-13 | 국민대학교산학협력단 | Method and apparatus for estimating location of vehicle using optical camera communication |
| CN109345015A (en) * | 2018-09-30 | 2019-02-15 | 百度在线网络技术（北京）有限公司 | Method and apparatus for choosing route |
| CN110852250A (en) * | 2019-11-07 | 2020-02-28 | 厦门市美亚柏科信息股份有限公司 | Vehicle weight removing method and device based on maximum area method and storage medium |
| CN111025365A (en) * | 2019-12-24 | 2020-04-17 | 东南大学 | Method for assisting in high-precision positioning of vehicle by two adjacent street lamps |
| CN111505577A (en) * | 2020-04-27 | 2020-08-07 | 湖南大学 | Mobile vehicle positioning method based on visible light communication |
Non-Patent Citations (2)
| Title |
|---|
| 一种基于视觉信息的可见光通信室内定位方法;王语琪;巩应奎;;计算机技术与发展(01);正文 * |
| 采用半导体光放大器进行直接调制的全双工光纤无线通信系统实验研究;何晶;文鸿;雷小燕;陈林;余建军;文双春;;通信学报(03);正文 * |
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