A vehicle positioning method and related device
By using orthogonal frequency division multiple access communication and super-resolution algorithm processing between roadside units and vehicle-mounted units, the problems of signal interference and separation difficulties in multi-vehicle positioning are solved, achieving high-precision and stable vehicle positioning results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- LIUZHOU WULING NEW ENERGY VEHICLE CO LTD
- Filing Date
- 2026-04-28
- Publication Date
- 2026-06-30
AI Technical Summary
Existing vehicle positioning technologies struggle to achieve efficient, synchronous, and high-precision collaborative positioning in multi-vehicle, high-density scenarios, exhibiting issues such as signal interference, separation difficulties, and low resource utilization efficiency.
By employing orthogonal frequency division multiple access (OFDM) technology and super-resolution algorithms, and through side link communication between roadside units and vehicle-mounted units, uplink reference signals from multiple vehicle-mounted units are received and separated. The super-resolution algorithm is then used to process the channel frequency response to obtain the angle of arrival and distance of arrival, thereby achieving high-precision positioning.
It has achieved high-precision, high-concurrency location positioning of multiple vehicles in dense, dynamic vehicle-to-everything (V2X) environments, improving traffic safety and efficiency, and adapting to stable operation in complex urban environments.
Smart Images
Figure CN122317536A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle positioning technology, and in particular to a vehicle positioning method and related apparatus. Background Technology
[0002] In the field of vehicle positioning technology, existing technologies mainly revolve around single-user network-assisted positioning based on 5G / C-V2X. However, these technologies have significant shortcomings in multi-vehicle, high-density scenarios. Specifically: existing multiple access methods struggle to effectively coordinate multi-user signal transmission, easily leading to mutual interference and difficulties in signal separation; parameter estimation algorithms have limited resolution capabilities in complex urban environments, failing to meet high-precision positioning requirements; and communication and positioning functions are designed relatively independently, resulting in low resource utilization and system coordination efficiency. These limitations make it difficult for existing technologies to support centralized, synchronous, and high-precision perception and positioning of multiple vehicles within a road network, thus hindering the further development of intelligent transportation systems.
[0003] Therefore, how to achieve efficient multi-vehicle cooperative positioning has become an important technical problem that urgently needs to be solved in the field of vehicle positioning technology. Summary of the Invention
[0004] To address the aforementioned issues, this application provides a vehicle positioning method that enables centralized, high-precision perception of multiple vehicles within a road network, effectively improving traffic safety and efficiency.
[0005] The embodiments of this application disclose the following technical solutions: The first aspect of this application provides a vehicle positioning method, which is applied to a roadside unit, the roadside unit communicating with an on-board unit via an orthogonal frequency division multiple access (OFDM) side link; the on-board unit is deployed on a vehicle, and there is a one-to-one correspondence between the on-board unit and the vehicle; the method includes: Simultaneously receive multiple uplink reference signals transmitted from multiple vehicle-mounted units; any two uplink reference signals are orthogonal signals; Channel estimation and channel separation are performed on the multiple uplink reference signals to obtain the channel frequency response corresponding to each vehicle unit; The channel frequency response corresponding to each vehicle unit is processed using a super-resolution algorithm to obtain the angle of arrival and distance of arrival corresponding to each vehicle unit; Based on the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit, the position of the vehicle corresponding to the vehicle-mounted unit in the coordinate system corresponding to the roadside unit is determined.
[0006] In one optional implementation, the step of performing channel estimation and channel separation on the plurality of uplink reference signals to obtain the channel frequency response corresponding to each of the vehicle-mounted units includes: The total channel frequency response is obtained by performing a Fourier transform on the multiple uplink reference signals in the frequency domain. For each vehicle-mounted unit, the channel frequency response corresponding to that vehicle-mounted unit is extracted from the total channel frequency response based on the preset frequency index set corresponding to that vehicle-mounted unit.
[0007] In one optional implementation, the step of processing the channel frequency response corresponding to each vehicle-mounted unit using a super-resolution algorithm to obtain the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit includes: Perform an inverse Fourier transform on the channel frequency response corresponding to each vehicle unit to obtain the channel response pulse corresponding to each vehicle unit; By using the multi-antenna array of the vehicle-mounted unit, a covariance matrix corresponding to each vehicle-mounted unit is constructed based on the channel impulse response corresponding to each vehicle-mounted unit; Eigenvalue decomposition is performed on the covariance matrix corresponding to each vehicle unit to obtain the signal subspace and noise subspace corresponding to each vehicle unit. Based on the super-resolution algorithm, the signal subspace and noise subspace corresponding to each vehicle unit are processed to obtain multiple paths corresponding to each vehicle unit, as well as the angle of arrival and delay corresponding to each path; Based on the multiple paths corresponding to each vehicle-mounted unit, and the angle of arrival and delay corresponding to each path, the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit are determined.
[0008] In one optional implementation, determining the angle of arrival and distance of arrival for each vehicle-mounted unit based on multiple paths corresponding to each vehicle-mounted unit, and the angle of arrival and delay corresponding to each path, includes: For each vehicle-mounted unit, the path with the shortest delay among the multiple paths corresponding to that vehicle-mounted unit is taken as the first path to reach that vehicle-mounted unit. For each of the vehicle-mounted units, the product of the delay corresponding to the first path of the vehicle-mounted unit and the speed of light is taken as the arrival distance of the vehicle-mounted unit. For each vehicle-mounted unit, the angle of arrival corresponding to the first path of the vehicle-mounted unit is taken as the angle of arrival of the vehicle-mounted unit.
[0009] In one optional implementation, determining the position of the vehicle corresponding to each onboard unit in the coordinate system corresponding to the roadside unit, based on the angle of arrival and distance of arrival corresponding to each onboard unit, includes: The angle of arrival and distance of arrival corresponding to each vehicle unit are used as the polar coordinates corresponding to each vehicle unit; The polar coordinates corresponding to the vehicle-mounted unit are transformed into two-dimensional Cartesian coordinates with the roadside unit as the origin, so as to obtain the position of the vehicle corresponding to the vehicle-mounted unit in the coordinate system corresponding to the roadside unit.
[0010] In one alternative implementation, the super-resolution algorithm is a multiple signal classification algorithm or a signal parameter estimation algorithm based on rotation invariant techniques.
[0011] In one alternative implementation, the method further includes: Configure a corresponding target vehicle-mounted unit maintenance list for the roadside unit, and periodically divide each vehicle-mounted unit in the target vehicle-mounted unit maintenance list into a set of orthogonal orthogonal frequency division multiple access subcarriers and transmission time slots based on positioning requirements; the target vehicle-mounted unit maintenance list includes information on vehicle-mounted units that need to be located within the communication range of the roadside unit.
[0012] A second aspect of this application provides a vehicle positioning device, the device being applied to a roadside unit, the roadside unit communicating with an on-board unit via an orthogonal frequency division multiple access (OFDM) side link; the on-board unit is deployed on a vehicle, and there is a one-to-one correspondence between the on-board unit and the vehicle; the device includes: The reference signal acquisition module is used to simultaneously receive multiple uplink reference signals transmitted from multiple vehicle-mounted units; any two uplink reference signals are orthogonal signals; The first data processing module is used to perform channel estimation and channel separation on the multiple uplink reference signals to obtain the channel frequency response corresponding to each vehicle unit. The second data processing module is used to process the channel frequency response corresponding to each vehicle unit using a super-resolution algorithm to obtain the angle of arrival and distance of arrival corresponding to each vehicle unit. The location determination module is used to determine the position of the vehicle corresponding to each vehicle-mounted unit in the coordinate system corresponding to the roadside unit based on the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit.
[0013] A third aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any implementation of the first aspect.
[0014] A fourth aspect of this application provides an electronic device, comprising: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method described in any implementation of the first aspect.
[0015] Compared with the prior art, this application has the following beneficial effects: This application provides a vehicle positioning method, which includes: a roadside unit communicating with multiple on-board units via an orthogonal frequency division multiple access (OFDM) lateral link, and receiving multiple uplink reference signals simultaneously transmitted by these on-board units. The roadside unit performs channel estimation and separation on the received uplink reference signals to obtain the independent channel frequency response corresponding to each on-board unit. The roadside unit uses a super-resolution algorithm to process each independent channel frequency response to obtain the angle of arrival and distance of arrival of each on-board unit signal to the roadside unit. Based on the angle of arrival and distance of arrival of each on-board unit, the roadside unit determines the two-dimensional position coordinates of the vehicle corresponding to each on-board unit in its coordinate system through coordinate transformation.
[0016] Because this application employs orthogonal frequency division multiple access (OFDMA) technology, the uplink reference signals of multiple vehicle units can be transmitted in parallel on mutually orthogonal subcarriers, thereby achieving natural and interference-free separation of multi-user signals at the physical layer. Therefore, the method of this application can efficiently and synchronously receive and separate the channel state information of multiple vehicles without relying on complex scheduling algorithms or significantly increasing control signaling overhead. Ultimately, it achieves high-precision and high-concurrency location positioning of multiple vehicles in a dense and dynamic vehicle network environment. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a schematic diagram of the topology of a vehicle positioning system provided in an embodiment of this application; Figure 2 A flowchart illustrating a vehicle positioning method provided in this application embodiment; Figure 3 This is a schematic diagram of the structure of a vehicle positioning device provided in an embodiment of this application. Detailed Implementation
[0019] As mentioned earlier, in the field of vehicle positioning technology, existing technologies mainly revolve around single-user network-assisted positioning based on 5G / C-V2X. However, these technologies have significant shortcomings in multi-vehicle, high-density scenarios. Specifically: existing multiple access methods struggle to effectively coordinate multi-user signal transmission, easily leading to mutual interference and making signal separation difficult; parameter estimation algorithms have limited resolution capabilities in complex urban environments, failing to meet high-precision positioning requirements; and communication and positioning functions are designed relatively independently, resulting in low resource utilization and system coordination efficiency. These limitations make it difficult for existing technologies to support centralized, synchronous, and high-precision perception and positioning of multiple vehicles within a road network, thus hindering the further development of intelligent transportation systems.
[0020] Therefore, how to achieve efficient multi-vehicle cooperative positioning has become an important technical problem that urgently needs to be solved in the field of vehicle positioning technology.
[0021] Based on this, this application provides a vehicle positioning method, which includes: a roadside unit communicating with multiple on-board units via an orthogonal frequency division multiple access (OFDM) lateral link, and receiving multiple uplink reference signals simultaneously transmitted by these on-board units. The roadside unit performs channel estimation and separation on the received uplink reference signals to obtain the independent channel frequency response corresponding to each on-board unit. The roadside unit uses a super-resolution algorithm to process each independent channel frequency response to obtain the angle of arrival and distance of arrival of each on-board unit signal to the roadside unit. Based on the angle of arrival and distance of arrival of each on-board unit, the roadside unit determines the two-dimensional position coordinates of the vehicle corresponding to each on-board unit in its coordinate system through coordinate transformation.
[0022] Because this application employs orthogonal frequency division multiple access (OFDMA) technology, the uplink reference signals of multiple vehicle units can be transmitted in parallel on mutually orthogonal subcarriers, thereby achieving natural and interference-free separation of multi-user signals at the physical layer. Therefore, the method of this application can efficiently and synchronously receive and separate the channel state information of multiple vehicles without relying on complex scheduling algorithms or significantly increasing control signaling overhead. Ultimately, it achieves high-precision and high-concurrency location positioning of multiple vehicles in a dense and dynamic vehicle network environment.
[0023] To facilitate understanding of the technical solutions in this application, the technical terms used in this application will be explained first.
[0024] Orthogonal Frequency Division Multiple Access (OFDMA) is an efficient multiple access technology in wireless communication. Its core principle is to divide the available channel bandwidth into a large number of mutually orthogonal narrowband subcarriers and dynamically allocate these subcarrier resources to different users, so that multiple users can transmit data in parallel through their respective allocated subcarrier sets in the same time period, thereby achieving efficient sharing of spectrum resources and concurrent access.
[0025] A Global Navigation Satellite System (GNSS) is a radio positioning, navigation, and timing system consisting of a constellation of satellites covering the globe or a region.
[0026] Vehicle-to-Infrastructure (V2I) is an important component of the Internet of Vehicles, specifically referring to the real-time two-way information interaction between vehicles and road infrastructure (such as roadside units, traffic signal control systems, and sensing devices) through wireless communication.
[0027] Vehicle-to-vehicle (V2V) communication is a wireless connectivity technology based on dedicated short-range communication that allows vehicles to exchange safety status information such as location, speed, and direction, as well as driving intentions in real time via a direct communication link without the need for network infrastructure relay.
[0028] An on-board unit (OBU) is an integrated intelligent terminal installed inside or outside a vehicle to enable V2X wireless communication, data exchange, and collaborative control functions between the vehicle and the outside world (including other vehicles, roadside facilities, pedestrians, and networks).
[0029] A roadside unit (RSU) is a fixed infrastructure device deployed along a road. As a core roadside node in a vehicle-to-everything (V2X) system, it provides wireless communication access, data interaction, local computing, and collaborative control services to onboard units.
[0030] Channel State Information (CSI) is quantitative information characterizing the transmission characteristics of a wireless channel, including key parameters such as path loss, delay spread, phase change, and Doppler shift experienced by the signal during propagation. It is the fundamental data for achieving high-performance demodulation and accurate positioning in wireless communication systems.
[0031] Time-of-Arrival (ToA) refers to the actual propagation time of a wireless signal in space from the transmitter to the receiver.
[0032] The Time Difference of Arrival (TDoA) is the time difference between the arrival of a signal transmitted from the same source at two or more different receivers.
[0033] Sidelink is a wireless communication mode defined in the 5G NR-V2X and LTE-V2X communication standards. It specifically refers to a communication link that can be established directly between terminal devices without the need for base station forwarding. It supports direct data transmission, collaborative sensing, and relative positioning in scenarios such as between vehicle units and between vehicle and pedestrian terminals.
[0034] A resource block (RB) is the most basic radio resource scheduling unit in an OFDMA system. It consists of a set of continuous time-frequency resources, including a fixed number of continuous subcarriers and a set of continuous OFDM symbols.
[0035] Orthogonal subcarriers are a set of mutually orthogonal frequency components used in orthogonal frequency division multiplexing systems. They ensure interference-free signal separation and demodulation at the receiver by satisfying strict mathematical orthogonality in the frequency domain.
[0036] A Localization Reference Signal (LRS) is a sequence of known signals designed for localization purposes, used to achieve channel estimation and localization parameter extraction.
[0037] Pilot sequences are known reference sequences that are predefined and inserted into the signal stream in a communication system. They are used by the receiver to estimate the wireless channel, synchronize the signal, and perform demodulation calibration.
[0038] Channel Impulse Response (CIR) is a function that describes the channel's response to instantaneous impulse signals, reflecting the time delay and amplitude information of multipath signals.
[0039] The Geometric Channel Model (GCM) abstracts the wireless signal propagation process into a geometric space structure consisting of a transmitter, receiver, and reflector. It uses modeling methods such as ray tracing to establish the relationship between the multipath components of the signal and the physical location of the transmitter and receiver in terms of parameters such as propagation delay and angle of arrival.
[0040] Super-Resolution Algorithms (SRA) are a class of high-precision signal parameter estimation algorithms. By utilizing the spatial characteristics of signals and mathematical optimization methods, they can achieve resolutions for parameters such as angle of arrival and time of arrival that exceed the performance limits of traditional Fourier or correlation methods. In multipath environments, they can effectively separate dense multipath components and estimate parameters with high precision.
[0041] Multiple Signal Classification (MUSIC) is a high-resolution spectral estimation method that uses the eigenvalue decomposition of the covariance matrix of the data received by the antenna array to accurately estimate the angle of arrival of the signal.
[0042] An antenna array is a system composed of multiple antenna elements arranged in a specific geometric structure, and it is the hardware basis for estimating the angle of arrival of a signal.
[0043] The angle of arrival (AoA) is the angle at which a signal arrives at the receiving antenna array, used to determine the direction of the signal.
[0044] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.
[0045] Figure 1 This is a schematic diagram of the topology of a vehicle positioning system provided in an embodiment of this application. Figure 1 The image clearly illustrates a typical application scenario of this application: a roadside unit (RSU) is deployed on the side of the road and establishes a connection with multiple vehicles traveling on the road through a wireless communication link represented by the dashed line. Each vehicle is equipped with an on-board unit (OBU).
[0046] A roadside unit is a fixed communication and computing infrastructure deployed along a road; the vehicle positioning method in this application is applied to this roadside unit. The roadside unit in this application has OFDMA uplink receiving capability, precise clock synchronization, multi-antenna arrays (such as uniform linear array ULA / uniform area array UPA), and a high-performance channel parameter processing unit.
[0047] The vehicle-mounted unit in this application has OFDMA side link communication capability and can send positioning reference signals according to the scheduling of the roadside unit.
[0048] In this application, the roadside unit communicates with the vehicle-mounted unit via an orthogonal frequency division multiple access (OFDM) side link.
[0049] Before the scheduling and resource allocation phase, a corresponding target vehicle unit maintenance list is configured for the roadside unit, and a set of orthogonal orthogonal frequency division multiple access subcarriers and transmission time slots are periodically allocated to each vehicle unit in the target vehicle unit maintenance list based on positioning requirements.
[0050] The target vehicle unit maintenance list includes information on the vehicle units that need to be located within the roadside unit communication range (vehicle unit identifier), as well as the set of subcarriers and transmission time slots allocated to each vehicle unit for orthogonal frequency division multiple access.
[0051] The advantage of allocating an orthogonal subcarrier set and transmission time slot to each vehicle unit is that it can ensure that the subcarrier sets of different vehicle units do not intersect at all within the same transmission time slot. This avoids interference between multi-user signals at the physical layer and ensures the orthogonality of the uplink reference signal in the frequency domain, thus laying the foundation for subsequent accurate channel separation and high-precision parameter estimation.
[0052] Each vehicle-mounted unit in this application modulates a positioning reference signal on its assigned set of subcarriers. This positioning reference signal possesses excellent autocorrelation and low cross-correlation characteristics.
[0053] Based on the above, combined with Figure 2 The vehicle positioning method provided in this application includes: S201, simultaneously receiving multiple uplink reference signals transmitted from multiple vehicle-mounted units.
[0054] The uplink reference signal in this application is a signal transmitted by the on-board unit, loaded onto its assigned set of orthogonal subcarriers, used to characterize its own channel characteristics so that the roadside unit can perform high-precision channel estimation and parameter extraction. Since the subcarrier sets assigned to each on-board unit are mutually orthogonal, any two uplink reference signals are orthogonal signals.
[0055] Specifically, after determining the target vehicle unit maintenance list, the roadside unit schedules orthogonal uplink OFDMA positioning resources (i.e., allocates specific orthogonal subcarrier sets and transmission time slots) to each vehicle unit in the list through the downlink control channel; multiple vehicle units synchronously send uplink reference signals to the roadside unit on their respective allocated orthogonal resources; the roadside unit uses its OFDMA receiver architecture to simultaneously receive multiple uplink reference signals transmitted from multiple vehicle units.
[0056] It should be noted that in multi-user scenarios, in order to ensure the efficiency and orthogonality of multiple vehicle-mounted units accessing the roadside unit simultaneously, this application adopts an uplink OFDMA access mechanism.
[0057] S202, perform channel estimation and channel separation on the multiple uplink reference signals to obtain the channel frequency response corresponding to each vehicle unit.
[0058] After receiving multiple uplink reference signals from multiple vehicle-mounted units, the roadside unit needs to process the received mixed uplink reference signals to accurately separate and obtain the independent channel characteristics of each vehicle-mounted unit from the mixed signals, thereby providing clean input data for independent high-precision parameter estimation for each vehicle.
[0059] Specifically, the roadside unit performs a Fourier transform on multiple uplink reference signals in the frequency domain to obtain the total channel frequency response; for each vehicle-mounted unit, the channel frequency response corresponding to that vehicle-mounted unit is extracted from the total channel frequency response based on the preset frequency index set corresponding to that vehicle-mounted unit.
[0060] For example, suppose the roadside unit assigns subcarrier indices 1-4 to vehicle-to-everything (V2X) unit and subcarrier indices 5-8 to V2X unit B. At the receiving end, the roadside unit performs a Fast Fourier Transform (FFT) on the received mixed signal to obtain a total channel frequency response containing the frequency responses of 8 subcarriers. Then, based on pre-defined scheduling information, the roadside unit precisely extracts the frequency domain responses at indices 1-4 from the total channel frequency response and uses them as the independent channel frequency response for V2X unit A; similarly, it extracts the frequency domain responses at indices 5-8 and uses them as the independent channel frequency response for V2X unit B. In this way, the mixed signals, which originally overlapped in the time and frequency domains, are efficiently and interference-free separated in the frequency domain based on orthogonal subcarrier allocation, thus laying the foundation for subsequent independent super-resolution parameter estimation for each vehicle.
[0061] S203, using a super-resolution algorithm to process the channel frequency response corresponding to each vehicle-mounted unit, to obtain the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit.
[0062] After determining the channel frequency response corresponding to each vehicle-mounted unit, the roadside unit can use a super-resolution algorithm (multiple signal classification algorithm or signal parameter estimation algorithm based on rotation invariant technology) to process the channel frequency response corresponding to each vehicle-mounted unit, thereby obtaining the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit.
[0063] In this application, the angle of arrival refers to the angle between the signal from the vehicle-mounted unit to the roadside unit and the normal direction of the roadside unit's antenna array, and is used to characterize the azimuth information of the vehicle-mounted unit relative to the roadside unit.
[0064] The distance of arrival in this application refers to the straight-line distance that a signal travels from the vehicle-mounted unit to the roadside unit. It is calculated by multiplying the signal's flight time by the speed of light and is used to characterize the relative distance between the vehicle-mounted unit and the roadside unit.
[0065] In one optional implementation, a super-resolution algorithm is used to process the channel frequency response corresponding to each vehicle-mounted unit to obtain the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit, including: The first step is to perform an inverse Fourier transform on the channel frequency response corresponding to each vehicle-mounted unit to obtain the channel response pulse corresponding to each vehicle-mounted unit.
[0066] An inverse Fourier transform is performed on the independent channel frequency response of each vehicle unit to transform it from the frequency domain to the time domain. The transformation result is the channel impulse response corresponding to that vehicle unit, which is presented as multiple peaks in the time domain. Each peak corresponds to a possible physical propagation path (such as a direct path, a reflected path, etc.), and the time delay position of the peak implies the path length information.
[0067] The second step involves constructing the covariance matrix for each vehicle-mounted unit based on the channel impulse response of each unit using the multi-antenna array of the vehicle-mounted unit.
[0068] By utilizing multiple time-domain signals (i.e., channel impulse responses sampled on different antennas) received by the antenna array of the roadside unit belonging to the same on-board unit, the statistical correlation of these signal samples is calculated. Treating each signal as a random process, a covariance matrix characterizing the spatial correlation of the signals is formed by calculating their autocorrelation and cross-correlation values. This matrix captures the phase and amplitude relationships of the signals across different antennas, and its mathematical structure implicitly contains information about the signal's direction of arrival.
[0069] The third step is to perform eigenvalue decomposition on the covariance matrix corresponding to each vehicle unit to obtain the signal subspace and noise subspace corresponding to each vehicle unit.
[0070] The covariance matrix is decomposed into eigenvalues and corresponding eigenvectors. The space spanned by the eigenvectors corresponding to the larger eigenvalues is identified as the signal subspace, which is theoretically spanned by the steering vectors of the real signal sources (i.e., multipath components). The space spanned by the eigenvectors corresponding to the smaller and similar eigenvalues is identified as the noise subspace, which is theoretically orthogonal to the steering vectors of all real signal sources.
[0071] The fourth step involves processing the signal subspace and noise subspace corresponding to each vehicle unit based on the super-resolution algorithm, to obtain multiple paths corresponding to each vehicle unit, as well as the angle of arrival and delay corresponding to each path.
[0072] Taking a multiple signal classification algorithm as an example, the orthogonality principle between the signal steering vector and the noise subspace is used to perform spectral peak search in a two-dimensional parameter space composed of angle and time delay. For each angle-time delay pair in the search grid, the degree of orthogonality between its steering vector and the noise subspace is calculated, and a spatial spectrum is generated. The peak position of the spatial spectrum corresponds to the estimated multipath parameter.
[0073] By searching in the angle-delay joint domain, peaks orthogonal to the noise subspace are found, thereby super-resolution estimation of the angle of arrival and flight time (i.e. delay) of all multipath components.
[0074] The fifth step is to determine the angle of arrival and distance of arrival for each vehicle unit based on the multiple paths corresponding to each vehicle unit, as well as the angle of arrival and delay corresponding to each path.
[0075] For each vehicle-mounted unit, the path with the shortest delay among the multiple paths corresponding to the vehicle-mounted unit is taken as the first path of arrival for that vehicle-mounted unit; the product of the delay corresponding to the first path of arrival for that vehicle-mounted unit and the speed of light is taken as the arrival distance corresponding to that vehicle-mounted unit; and the angle of arrival corresponding to the first path of arrival for that vehicle-mounted unit is taken as the angle of arrival corresponding to that vehicle-mounted unit.
[0076] In typical line-of-sight propagation environments, the signal that first reaches the receiver (i.e., the first path of arrival) is most likely a direct path, and its propagation delay and angle most directly reflect the true geometric relationship between the vehicle-mounted unit and the roadside unit. Using the first path of arrival parameter for calculation can effectively avoid errors caused by multipath signals reflected from objects such as walls and vehicles, thereby significantly improving the accuracy and reliability of positioning results. This is a key decision for achieving high-precision, robust positioning.
[0077] S204, based on the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit, determine the position of the vehicle corresponding to the vehicle-mounted unit in the coordinate system corresponding to the roadside unit.
[0078] Specifically, the arrival angle and arrival distance corresponding to each vehicle-mounted unit are used as the polar coordinates of each vehicle-mounted unit; the polar coordinates of the vehicle-mounted unit are converted into two-dimensional Cartesian coordinates with the roadside unit as the origin, so as to obtain the position of the vehicle corresponding to the vehicle-mounted unit in the coordinate system corresponding to the roadside unit.
[0079] For example, suppose the roadside unit receives a report from the vehicle-mounted unit OBU1 that the angle of arrival is 30 degrees and the distance of arrival is 50 meters; then the polar coordinates of the vehicle-mounted unit OBU1 are (30°, 50m).
[0080] In the roadside unit coordinate system, the origin (0, 0) is taken as its own position, the positive Y-axis is taken as the direction of the array normal (e.g., due north), and the positive X-axis is taken as the vertical direction.
[0081] The polar coordinates corresponding to the on-board unit OBU1 are transformed into two-dimensional Cartesian coordinates with the roadside unit as the origin, thus obtaining the position of the vehicle corresponding to the on-board unit OBU1 in the coordinate system corresponding to the roadside unit. The specific transformation formula is as follows: X coordinate = distance to reach × sin(angle of arrival) = 25 meters; Y coordinate = distance to reach × cos(angle of arrival) = 43.4 meters.
[0082] Therefore, the vehicle corresponding to OBU1 is located at (25, 43, 30) in the roadside unit coordinate system. Similarly, for other vehicle-mounted units, their two-dimensional positions in the same coordinate system can be calculated through the same transformation process based on their respective angles of arrival and distances of arrival, thereby achieving high-precision positioning of multiple vehicles under a unified geographic reference.
[0083] In summary, the vehicle positioning method provided in this application has at least the following advantages: First, it offers high positioning accuracy. The vehicle positioning method provided in this application utilizes the broadband characteristics of orthogonal frequency division multiple access (OFDMA) technology, combined with super-resolution signal processing algorithms, to perform high-precision joint estimation of the signal's angle of arrival and time of flight. Its positioning accuracy can reach the centimeter level, surpassing the positioning performance of traditional global navigation satellite systems in complex urban environments. It can effectively meet the stringent requirements for high-precision positioning in application scenarios such as advanced autonomous driving, precise lane control, and vehicle-to-everything (V2X) communication.
[0084] Second, it boasts high reliability. The vehicle positioning method provided in this application achieves positioning functionality based on the vehicle-road cooperative side-link, without relying on satellite navigation signals. Therefore, even in typical complex environments such as urban canyons, underground parking lots, and tunnels where satellite signals are severely blocked, attenuated, or interfered with, this method can still operate stably and reliably. It effectively compensates for the limitations of a single satellite positioning system in specific scenarios, significantly improving the all-weather, all-scenario availability and robustness of vehicle positioning services.
[0085] Based on the same inventive concept, this application also provides a vehicle positioning device. Figure 3 This is a schematic diagram of a vehicle positioning device provided in an embodiment of this application. (In conjunction with...) Figure 3 As shown, the vehicle positioning device 300 provided in this application includes: The reference signal acquisition module 301 is used to simultaneously receive multiple uplink reference signals transmitted from multiple vehicle-mounted units; any two uplink reference signals are orthogonal signals. The first data processing module 302 is used to perform channel estimation and channel separation on the plurality of uplink reference signals to obtain the channel frequency response corresponding to each vehicle unit; The second data processing module 303 is used to process the channel frequency response corresponding to each vehicle unit using a super-resolution algorithm to obtain the angle of arrival and distance of arrival corresponding to each vehicle unit. The position determination module 304 is used to determine the position of the vehicle corresponding to the vehicle unit in the coordinate system corresponding to the roadside unit based on the angle of arrival and distance of arrival corresponding to each vehicle unit.
[0086] In one alternative implementation, the first data processing module includes: The first data processing unit is used to perform Fourier transform on the plurality of uplink reference signals in the frequency domain to obtain the total channel frequency response; The second data processing unit is used to extract the channel frequency response corresponding to each vehicle unit from the total channel frequency response based on the preset frequency index set corresponding to the vehicle unit.
[0087] In one alternative implementation, the second data processing module includes: The third data processing unit is used to perform an inverse Fourier transform on the channel frequency response corresponding to each vehicle unit to obtain the channel response pulse corresponding to each vehicle unit. The fourth data processing unit is used to construct the covariance matrix corresponding to each vehicle unit based on the channel impulse response corresponding to each vehicle unit through the multi-antenna array of the vehicle unit; The fifth data processing unit is used to perform eigenvalue decomposition on the covariance matrix corresponding to each vehicle unit to obtain the signal subspace and noise subspace corresponding to each vehicle unit. The sixth data processing unit is used to process the signal subspace and noise subspace corresponding to each vehicle unit based on the super-resolution algorithm to obtain multiple paths corresponding to each vehicle unit, as well as the angle of arrival and delay corresponding to each path; The seventh data processing unit is used to determine the angle of arrival and distance of arrival for each vehicle unit based on the multiple paths corresponding to each vehicle unit, and the angle of arrival and delay corresponding to each path.
[0088] In one alternative implementation, the seventh data processing unit includes: The first-path determination subunit is used to determine the path with the shortest delay among the multiple paths corresponding to each vehicle unit as the first-path of that vehicle unit. The arrival distance determination subunit is used to take the product of the delay and the speed of light corresponding to the first path of the vehicle unit as the arrival distance of the vehicle unit for each vehicle unit. An angle of arrival determination subunit is used to determine the angle of arrival corresponding to the first path of each vehicle-mounted unit as the angle of arrival of that vehicle-mounted unit.
[0089] In one alternative implementation, the location determination module includes: A polar coordinate determination unit is used to take the angle of arrival and the distance of arrival corresponding to each vehicle unit as the polar coordinates corresponding to each vehicle unit; The vehicle position determination unit is used to transform the polar coordinates corresponding to the vehicle-mounted unit to two-dimensional Cartesian coordinates with the roadside unit as the origin, so as to obtain the position of the vehicle corresponding to the vehicle-mounted unit in the coordinate system corresponding to the roadside unit.
[0090] In one alternative implementation, the vehicle positioning device 300 further includes: The information configuration unit is used to configure a corresponding target vehicle-mounted unit maintenance list for the roadside unit, and periodically divide each vehicle-mounted unit in the target vehicle-mounted unit maintenance list into a set of orthogonal orthogonal frequency division multiple access subcarriers and transmission time slots based on positioning requirements; the target vehicle-mounted unit maintenance list includes information on vehicle-mounted units that need to be located within the communication range of the roadside unit.
[0091] Based on the vehicle positioning method and apparatus provided in the foregoing embodiments, this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements some or all of the steps in the vehicle positioning method mentioned above.
[0092] Based on the vehicle positioning method and apparatus provided in the foregoing embodiments, this application also provides an electronic device, including: A memory on which computer programs are stored; A processor is configured to execute the computer program in the memory to implement some or all of the steps in the vehicle positioning method provided in the foregoing embodiments.
[0093] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separate. The components indicated as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment solution according to actual needs. Those skilled in the art can understand and implement this without creative effort.
[0094] The above description is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A vehicle positioning method characterized by comprising: The method is applied to a roadside unit, which communicates with the vehicle-mounted unit via a side link of orthogonal frequency division multiple access; The vehicle-mounted unit is deployed on the vehicle, and each vehicle-mounted unit corresponds one-to-one with the vehicle; the method includes: Simultaneously receive multiple uplink reference signals transmitted from multiple vehicle-mounted units; any two uplink reference signals are orthogonal signals; Channel estimation and channel separation are performed on the multiple uplink reference signals to obtain the channel frequency response corresponding to each vehicle unit; The channel frequency response corresponding to each vehicle unit is processed using a super-resolution algorithm to obtain the angle of arrival and distance of arrival corresponding to each vehicle unit; Based on the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit, the position of the vehicle corresponding to the vehicle-mounted unit in the coordinate system corresponding to the roadside unit is determined.
2. The method of claim 1, wherein, The step of performing channel estimation and channel separation on the plurality of uplink reference signals to obtain the channel frequency response corresponding to each of the vehicle-mounted units includes: The total channel frequency response is obtained by performing a Fourier transform on the multiple uplink reference signals in the frequency domain. For each vehicle-mounted unit, the channel frequency response corresponding to that vehicle-mounted unit is extracted from the total channel frequency response based on the preset frequency index set corresponding to that vehicle-mounted unit.
3. The method according to claim 1, characterized in that, The step of processing the channel frequency response corresponding to each vehicle-mounted unit using a super-resolution algorithm to obtain the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit includes: Perform an inverse Fourier transform on the channel frequency response corresponding to each vehicle unit to obtain the channel response pulse corresponding to each vehicle unit; By using the multi-antenna array of the vehicle-mounted unit, a covariance matrix corresponding to each vehicle-mounted unit is constructed based on the channel impulse response corresponding to each vehicle-mounted unit; Eigenvalue decomposition is performed on the covariance matrix corresponding to each vehicle unit to obtain the signal subspace and noise subspace corresponding to each vehicle unit. Based on the super-resolution algorithm, the signal subspace and noise subspace corresponding to each vehicle unit are processed to obtain multiple paths corresponding to each vehicle unit, as well as the angle of arrival and delay corresponding to each path; Based on the multiple paths corresponding to each vehicle-mounted unit, and the angle of arrival and delay corresponding to each path, the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit are determined.
4. The method according to claim 3, characterized in that, The step of determining the angle of arrival and distance of arrival for each vehicle-mounted unit based on multiple paths corresponding to each vehicle-mounted unit, and the angle of arrival and delay corresponding to each path, includes: For each vehicle-mounted unit, the path with the shortest delay among the multiple paths corresponding to that vehicle-mounted unit is taken as the first path to reach that vehicle-mounted unit. For each of the vehicle-mounted units, the product of the delay corresponding to the first path of the vehicle-mounted unit and the speed of light is taken as the arrival distance of the vehicle-mounted unit. For each vehicle-mounted unit, the angle of arrival corresponding to the first path of the vehicle-mounted unit is taken as the angle of arrival of the vehicle-mounted unit.
5. The method according to claim 1, characterized in that, The step of determining the position of the vehicle corresponding to each on-board unit in the coordinate system corresponding to the roadside unit based on the angle of arrival and distance of arrival of each on-board unit includes: The angle of arrival and distance of arrival corresponding to each vehicle unit are used as the polar coordinates corresponding to each vehicle unit; The polar coordinates corresponding to the vehicle-mounted unit are transformed into two-dimensional Cartesian coordinates with the roadside unit as the origin, so as to obtain the position of the vehicle corresponding to the vehicle-mounted unit in the coordinate system corresponding to the roadside unit.
6. The method according to claim 4, characterized in that, The super-resolution algorithm is a multiple signal classification algorithm or a signal parameter estimation algorithm based on rotation invariant technology.
7. The method according to claim 1, characterized in that, The method further includes: Configure a corresponding target vehicle-mounted unit maintenance list for the roadside unit, and periodically divide each vehicle-mounted unit in the target vehicle-mounted unit maintenance list into a set of orthogonal orthogonal frequency division multiple access subcarriers and transmission time slots based on positioning requirements; the target vehicle-mounted unit maintenance list includes information on vehicle-mounted units that need to be located within the communication range of the roadside unit.
8. A vehicle positioning device, characterized in that, The device is applied to a roadside unit, which communicates with the vehicle-mounted unit via an orthogonal frequency division multiple access (OFDM) side link. The vehicle-mounted unit is deployed on the vehicle, and each vehicle-mounted unit corresponds to a specific vehicle; the device includes: The reference signal acquisition module is used to simultaneously receive multiple uplink reference signals transmitted from multiple vehicle-mounted units; any two uplink reference signals are orthogonal signals; The first data processing module is used to perform channel estimation and channel separation on the multiple uplink reference signals to obtain the channel frequency response corresponding to each vehicle unit. The second data processing module is used to process the channel frequency response corresponding to each vehicle unit using a super-resolution algorithm to obtain the angle of arrival and distance of arrival corresponding to each vehicle unit. The location determination module is used to determine the position of the vehicle corresponding to each vehicle-mounted unit in the coordinate system corresponding to the roadside unit based on the angle of arrival and distance of arrival corresponding to each vehicle-mounted unit.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method described in any one of claims 1-7.
10. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1-7.