Target object information statistical method and device, equipment, medium and product

Abstract

The embodiment of the invention discloses a target object information statistical method and device, equipment, a medium and a product. The method comprises the steps that a light beam device is used for dividing a modulated light signal into a transmitting light signal and a local oscillation light signal; the frequency of the modulated optical signal is a linear triangular wave; emitting the emission light signal to a target object in a target scene to determine an echo signal corresponding to the target object; determining target object information corresponding to the target object based on the local oscillation optical signal and the echo signal; the target object information comprises the moving speed of the target object relative to the FMCW laser radar and the distance between the target object and the FMCW laser radar. According to the technical scheme, the distance and the speed of the target object relative to the laser radar are determined by using the local oscillation signal generated by the laser radar and the echo signal reflected by the target object, interference of environmental factors on target object identification is avoided, and the efficiency and the accuracy of target object information statistics are improved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of laser radar technology, and in particular to a method, device, equipment, medium and product for collecting target information. Background Art

[0002] Automatically identifying moving objects like pedestrians and vehicles and counting their entry and exit is crucial in scenarios like urban traffic management and crowd monitoring in large commercial venues. Traditional visual image methods and ToF (Time of Flight)-based LiDAR technology have many limitations in their applications.

[0003] Traditional visual image methods primarily rely on deep learning algorithms to process camera-captured images to identify and count targets. However, this method requires extremely high computing power, and at night, in low-light conditions, infrared technology must be used to assist in image acquisition, which not only increases equipment cost but also can affect image quality. During the day, strong sunlight can easily cause image overexposure and shadow interference, reducing target recognition accuracy. Time-of-flight (ToF)-based lidar technology can directly measure the distance between the target and the radar, reducing the computing power required for target recognition compared to visual image methods. However, ToF lidar is susceptible to interference from ambient light, and strong ambient light can increase measurement errors. More critically, ToF lidar cannot obtain target speed and direction information from a single frame of data. In scenes with dense pedestrian and vehicle traffic, it is difficult to continuously track targets, and targets can be easily lost, affecting the accuracy and reliability of statistics. Summary of the Invention

[0004] The embodiments of the present disclosure provide a method, apparatus, device, medium, and product for collecting target information, which avoid interference with target identification caused by environmental factors and improve the efficiency and accuracy of collecting target information.

[0005] In a first aspect, a target object information statistics method is provided, comprising:

[0006] A beam splitter is used to separate a modulated optical signal into a transmitted optical signal and a local oscillator optical signal; the frequency of the modulated optical signal is a linear triangular wave;

[0007] Directing the emitted light signal toward a target object in a target scene to determine an echo signal corresponding to the target object;

[0008] The target object information corresponding to the target object is determined based on the local oscillator light signal and the echo signal; the target object information includes the moving speed of the target object relative to the FMCW laser radar and the distance between the target object and the FMCW laser radar.

[0009] In a second aspect, a target object information statistics device is provided, comprising:

[0010] A light splitting module, configured to use a beam splitter to split a modulated light signal into a transmitted light signal and a local oscillator light signal; the frequency of the modulated light signal is a linear triangular wave;

[0011] an echo signal determination module, configured to direct the emitted light signal toward a target object in a target scene to determine an echo signal corresponding to the target object;

[0012] A target information determination module is used to determine target information corresponding to the target based on the local oscillator light signal and the echo signal; the target information includes the moving speed of the target relative to the FMCW laser radar and the distance between the target and the FMCW laser radar.

[0013] According to a third aspect, an electronic device is provided, including:

[0014] at least one processor; and,

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the target object information statistics method as described in the first aspect above.

[0017] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the target object information statistics method as described in the first aspect above is implemented.

[0018] In a fifth aspect, a computer program product is provided, which includes a computer program, and when the computer program is executed by a processor, it implements the target object information statistics method as described in the first aspect above.

[0019] The disclosed embodiments disclose a method, apparatus, device, medium, and product for target object information statistics, the method comprising: using a beam splitter to divide a modulated light signal into a transmitted light signal and a local oscillator light signal; the frequency of the modulated light signal is a linear triangular wave; emitting the transmitted light signal to a target in a target scene to determine an echo signal corresponding to the target; determining target object information corresponding to the target based on the local oscillator light signal and the echo signal; the target object information includes the moving speed of the target relative to an FMCW laser radar and the distance between the target and the FMCW laser radar. This technical solution utilizes the local oscillator signal generated by the laser radar and the echo signal reflected by the target to determine the distance and speed of the target relative to the laser radar, thereby avoiding interference with target identification caused by environmental factors and improving the efficiency and accuracy of target object information statistics.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the embodiments of the present disclosure. Other features of the embodiments of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1 This is a flow chart of a target object information statistics method provided in the first embodiment of the present disclosure;

[0023] Figure 2 This is a schematic diagram of Doppler frequency shift provided by the first embodiment of the present disclosure;

[0024] Figure 3 This is a schematic diagram of a motion state recognition result of a moving target provided by the first embodiment of the present disclosure;

[0025] Figure 4 This is a schematic diagram of the structure of a target object information statistics device provided in the second embodiment of the present disclosure;

[0026] Figure 5 This is a structural diagram of an electronic device provided in Example 3 of the present disclosure. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solutions of the embodiments of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the embodiments described are only part of the embodiments of the present disclosure, not all of them. Based on the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the embodiments of the present disclosure.

[0028] It should be noted that the terms "first", "second", etc. in the description and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Example 1

[0030] Figure 1 This is a flow chart of a method for collecting target information statistics provided by the first embodiment of the present disclosure. This embodiment is applicable to the case of collecting statistics on target information. The method can be executed by a target information statistics device. The target information statistics device can be implemented in the form of hardware and / or software. The target information statistics device can be configured in an electronic device, including but not limited to computers, computers, terminals, servers and other devices with data processing capabilities. Figure 1 As shown, the method includes:

[0031] S110 , using a beam splitter to separate a modulated optical signal into a transmitted optical signal and a local oscillator optical signal; the frequency of the modulated optical signal is a linear triangular wave.

[0032] In this embodiment, the modulated optical signal may be an optical signal generated and modulated by a laser transmitter in a frequency-modulated continuous wave (FMCW) laser radar. In an FMCW laser radar, the frequency of the optical signal generated by the laser transmitter is modulated into a linear triangular wave form, that is, the frequency of the modulated optical signal changes linearly with time, forming a periodic triangular wave shape. The modulation method may be current modulation, temperature modulation and / or external modulator modulation. Among them, the FMCW laser radar may be a laser radar system that uses frequency modulated continuous wave technology to measure the distance and speed of a target. It measures the distance and speed of the target by modulating the frequency of the transmitted optical signal and analyzing the frequency difference between the reflected optical signal and the transmitted optical signal. Frequency modulation allows the frequency of the modulated optical signal to change linearly and periodically with time, laying the foundation for subsequent information extraction.

[0033] Specifically, a beam splitter can be used to split the modulated optical signal into a transmitted optical signal and a local oscillator optical signal. The beam splitter can be a beam splitter, which is an optical element typically made of special optical materials (such as a beam splitter prism or a semi-transparent, semi-reflective mirror) that can split a beam of light into two or more beams. The transmitted optical signal can be the optical signal used to illuminate the target after beam splitting, and the local oscillator optical signal can be the optical signal retained as a local reference signal after beam splitting.

[0034] It should be noted that LiDAR can obtain target information at every angle path within a target scene. Common scanning methods include mechanical rotation scanning, MEMS micro-vibration mirror scanning, and solid-state phased array scanning. Taking mechanical rotation scanning as an example, the laser transmitter and receiver are mounted on a rotatable structure, which transmits and receives laser signals at each angle through 360-degree uniform rotation. MEMS micro-vibration mirror scanning uses the rapid swing of micro-mirrors to achieve beam deflection in different directions, completing field of view coverage without relying on complex mechanical structures; solid-state phased array scanning is based on the principle of electronic control of beam direction. By adjusting the phase difference of the array antenna, the laser beam can be quickly scanned in space, with higher reliability and scanning speed.

[0035] S120: Direct the transmitted light signal toward a target object in the target scene to determine an echo signal corresponding to the target object.

[0036] In this embodiment, the target scene may be a scene where target object information statistics are required. For example, the target scene may be a scene such as urban traffic management or crowd flow monitoring in large commercial venues. Specifically, after obtaining a transmitted light signal, the transmitted light signal may be directed toward a target object in the target scene. The target object may reflect the transmitted light signal to obtain an echo signal. The echo signal may be the transmitted light signal after being reflected by the target object. The frequency of the echo signal may differ from that of the transmitted light signal due to the distance and movement of the target object.

[0037] S130. Determine target information corresponding to the target based on the local oscillator light signal and the echo signal; the target information includes the moving speed of the target relative to the FMCW laser radar and the distance between the target and the FMCW laser radar.

[0038] Specifically, after the echo signal is determined, the local oscillator (LO) light and the echo signal are coherently detected in an optical mixer. A photodetector captures the interference signal generated by the superposition of the LO light and the echo signal, and the frequency difference between the two is detected. Based on this frequency difference, the corresponding target information can be determined.

[0039] The target information includes the target's speed relative to the FMCW lidar and the distance between the target and the FMCW lidar. The target information can be stored as point cloud data, which is a collection of data used to represent the surface of an object or the entire space in three-dimensional space. Point cloud data can be composed of a large number of points, each of which contains specific three-dimensional coordinates (usually X, Y, and Z coordinates) and sometimes other attributes such as color, intensity, and normal direction.

[0040] It should be noted that the echo signal carries two important pieces of information relative to the local oscillator light signal: one is the light propagation delay caused by the distance between the target and the FMCW lidar, that is, the time difference in the round-trip light between the radar and the target. This time difference is directly related to the distance between the target and the FMCW lidar, and the distance can be calculated through correlation. The second piece of information is the Doppler shift caused by the target's movement speed. When the target approaches or moves away from the radar, the frequency of the echo signal will increase or decrease accordingly.

[0041] Figure 2 A schematic diagram of Doppler frequency shift provided in this embodiment is shown in FIG. Figure 2As shown, the frequency of the modulated optical signal is a linear triangular wave. The blue signal represents the local oscillator (LO) optical signal, the red signal represents the echo signal, and the green signal represents the frequency difference signal extracted from the echo and LO signals. In actual calculations, the frequency difference between the rising and falling edges of the triangular wave can be utilized. The frequency difference between the rising and falling echoes and the LO light differs due to the opposite Doppler shift directions. By analyzing and calculating these two frequency differences through a specific signal processing algorithm, we can accurately separate and obtain target range and velocity information.

[0042] This embodiment provides a method for collecting target information, including: using a beam splitter to separate a modulated light signal into a transmitted light signal and a local oscillator light signal; the frequency of the modulated light signal is a linear triangular wave; directing the transmitted light signal toward a target in a target scene to determine an echo signal corresponding to the target; and determining target information corresponding to the target based on the local oscillator light signal and the echo signal; the target information includes the target's speed relative to an FMCW laser radar and the distance between the target and the FMCW laser radar. This technical solution avoids interference with target identification caused by environmental factors and improves the efficiency and accuracy of target information collection.

[0043] As an optional implementation of this embodiment, the target object information statistics method provided in this embodiment further includes:

[0044] 1) When the target scene includes multiple targets, at least two moving targets are determined based on the movement speed of each target relative to the FMCW laser radar and a preset speed threshold.

[0045] Specifically, if there are multiple targets in the target scene, the target information of each target can be obtained based on the method provided in this embodiment. The target information includes the moving speed of the target relative to the FMCW laser radar and the distance between the target and the FMCW laser radar.

[0046] Continuing with the above description, at least two moving targets can be identified based on the speed of each target relative to the FMCW lidar and a preset speed threshold. The preset speed threshold can be a pre-set speed threshold that can be used to assess whether the target is stationary or in motion. For example, for any of the targets, the target's speed relative to the FMCW lidar can be compared with the preset speed threshold. If the target's speed relative to the FMCW lidar exceeds the preset speed threshold, the target can be considered to be in motion and identified as a moving target. If the target's speed relative to the FMCW lidar is below the preset speed threshold, the target can be considered to be stationary and identified as a background target. Using the preset speed threshold to filter out moving targets from the various targets reduces the amount of data required for subsequent analysis of moving targets, reduces data processing, and improves target recognition efficiency for stationary background objects in the target scene.

[0047] 2) Determine the inflow and outflow flow of the target scene based on the installation position of the FMCW laser radar and the frequency difference corresponding to each of the moving targets.

[0048] Specifically, after the moving target is identified, the installation location of the FMCW lidar can be determined. The inflow and outflow of the target scene can be determined based on the installation location of the FMCW lidar and the frequency difference corresponding to each moving target. The frequency difference can be the frequency difference between the local oscillator light signal and the echo signal corresponding to the moving target. By analyzing the frequency difference (Doppler shift) between the local oscillator light signal and the echo signal corresponding to the moving target, it can be determined whether the target is approaching or moving away from the radar. The Doppler shift refers to the difference between the frequency of the wave reflected by the target and the frequency emitted by the source when there is relative motion between the transmitting source and the target. Specifically, when the target approaches the radar, the frequency of the reflected signal increases, a phenomenon known as an "upward Doppler shift" or "positive Doppler shift." When the target moves away from the radar, the frequency of the reflected signal decreases, a phenomenon known as a "downward Doppler shift" or "negative Doppler shift."

[0049] As an optional implementation manner of this embodiment, determining the inbound and outbound traffic of the target scene based on the installation position of the FMCW lidar and the target object information corresponding to the moving targets in the moving target set includes:

[0050] 1) Determine the movement direction of each of the moving targets based on the installation position of the FMCW laser radar and the frequency difference corresponding to each of the moving targets.

[0051] Specifically, the motion state of the moving target relative to the FMCW lidar can be determined based on the frequency difference corresponding to the moving target. This motion state can include moving away from or approaching the FMCW lidar. Once the motion state is determined, the direction of movement of each moving target can be determined based on the installation location of the FMCW lidar and the motion state corresponding to each moving target. It should be noted that the direction of movement of the moving target, whether moving away from or approaching the moving target represented by the FMCW lidar, will vary depending on the installation location of the FMCW lidar.

[0052] For example, an FMCW lidar is installed at the entrance of a hotel lobby, and the target scene is the hotel lobby. If the difference between the frequency of the local oscillator light signal and the frequency of the echo signal corresponding to the moving target is positive, the frequency of the echo signal is considered to be lower than that of the local oscillator light signal, that is, the frequency of the signal reflected by the target has decreased (negative Doppler shift), and the moving target can be considered to be moving away from the FMCW lidar. If the frequency difference is negative, that is, the frequency of the signal reflected by the target has increased (i.e., a positive Doppler shift has occurred), then the moving target is moving toward the FMCW lidar.

[0053] Continuing with the above description, if the FMCW lidar is installed at the entrance to the hotel lobby and the moving target moves away from the FMCW lidar, it can be determined that the moving target is moving into the hotel lobby. If the FMCW lidar is installed at the entrance to the hotel lobby and the moving target moves close to the FMCW lidar, it can be determined that the moving target is moving out of the hotel lobby.

[0054] Taking the moving target as a human body image as an example, Figure 3 A schematic diagram of the motion state recognition result of a moving target provided in this embodiment is as follows: Figure 3As shown, the motion states of two adjacent human images are identified as approaching and moving away from the FMCW lidar, respectively. In a single frame of data, FMCW's detection of Doppler shift directly indicates whether a moving target is approaching or moving away from the FMCW lidar. The velocity of the moving target is also determined, allowing the static background to be removed. The approaching and moving away data can then be extracted for separate moving target identification (e.g., number recognition). This ensures that even two moving targets in close proximity are not identified as the same target. In dense pedestrian and vehicle traffic, the FMCW-based lidar target counting method can quickly and accurately identify moving targets and count the number of people entering and leaving the vehicle. Whether monitoring vehicle flow in real time at a traffic intersection or counting people entering and leaving a large shopping mall, this method operates stably and reliably, providing accurate data support for intelligent urban management and business decision-making. Compared to traditional methods, it offers greater environmental adaptability, lower computing power requirements, and superior target tracking and identification capabilities, demonstrating strong technical advantages and broad application prospects.

[0055] 2) Determine the inflow and outflow traffic of the target scene based on the movement direction of each of the moving targets.

[0056] Specifically, after the moving direction of each moving target object is obtained, the inflow and outflow traffic of the target scene can be determined based on the moving direction of the moving target object.

[0057] As an optional implementation manner of this embodiment, the determining the target information corresponding to the target based on the local oscillator light signal and the echo signal further includes:

[0058] 1) Determining a first moving target set and a second moving target set based on the moving directions of the moving targets, wherein the moving directions of the moving targets in the first target set and the second target set are opposite.

[0059] Specifically, after obtaining the motion direction of each moving target object, a first moving target set and a second moving target set can be determined based on the motion direction of each moving target object. The moving targets in the first moving target set have the same motion direction, the moving targets in the second moving target set have the same motion direction, and the moving targets in the first and second moving target sets have opposite motion directions.

[0060] 2) Determining the inflow and outflow traffic of the target scene based on the first target object set and the second target object set.

[0061] After obtaining the first target object set and the second target object set, the inflow and outflow traffic of the target scene may be determined based on the number of moving targets in the first target object set and the number of moving targets in the second target object set.

[0062] For example, the target scene can be the lobby of a shopping mall, and the installation location of the FMCW laser radar can be at the entrance of the shopping mall lobby. The movement direction of the first target object set is close to the FMCW laser radar. It can be considered that the moving targets in the first target object set are all going out of the mall. The movement direction of the second target object set is away from the FMCW laser radar. It can be considered that the moving targets in the second target object set are all going to enter the mall. The number of moving targets in the first target object set and the number of moving targets in the second target object set determine the inflow and outflow traffic of the mall.

[0063] As an optional implementation of this embodiment, determining the target object information corresponding to the target object based on the local oscillator light signal and the echo signal includes:

[0064] 1) Determine an electrical signal based on the local oscillator optical signal and the echo signal.

[0065] Specifically, after obtaining the local oscillation optical signal, the electrical signal may be determined through the local oscillation optical signal and the echo signal, wherein the frequency of the electrical signal may be the frequency difference between the echo signal and the local oscillation optical signal.

[0066] 2) Determining target object information corresponding to the target object based on the frequency of the electrical signal.

[0067] Continuing with the above description, after obtaining the electrical signal, the distance between the target object and the FMCW lidar can be calculated based on the frequency of the electrical signal and the modulation parameters of the FMCW lidar transmission signal (such as the bandwidth of the modulation frequency). By analyzing the rate of change of the frequency difference (Doppler shift), the moving speed of the target object relative to the radar is calculated, and then the target object information corresponding to the target object can be obtained.

[0068] As an optional implementation manner of this embodiment, determining the electrical signal based on the local oscillator optical signal and the echo signal includes:

[0069] 1) Using an optical mixer, the local oscillator light signal and the echo signal are superimposed to obtain an interference light signal, wherein the interference light signal carries the frequency difference between the local oscillator light signal and the echo signal corresponding to the target object.

[0070] Specifically, after obtaining the local oscillator light signal and the echo signal, an optical mixer may be used to superimpose the local oscillator light signal and the echo signal to obtain an interference light signal, which carries the frequency difference between the local oscillator light signal and the echo signal.

[0071] 2) Converting the interference light signal into the electrical signal using a photodetector.

[0072] Specifically, a photodetector may be used to convert the interference light signal into an electrical signal, and the frequency of the electrical signal is the frequency difference between the echo signal and the local oscillator light signal.

[0073] Example 2

[0074] Figure 4 is a structural diagram of a target object information statistics device provided in the second embodiment of the present disclosure; Figure 4 As shown, the device includes: a spectroscopic module 210 , an echo signal determination module 220 , and a target information determination module 230 .

[0075] The optical splitting module 210 is used to use a beam splitter to split the modulated optical signal into a transmission optical signal and a local oscillator optical signal; the frequency of the modulated optical signal is a linear triangular wave;

[0076] an echo signal determination module 220 for directing the transmitted light signal toward a target object in a target scene to determine an echo signal corresponding to the target object;

[0077] The target object information determination module 230 is used to determine the target object information corresponding to the target object based on the local oscillator light signal and the echo signal; the target object information includes the moving speed of the target object relative to the FMCW laser radar and the distance between the target object and the FMCW laser radar.

[0078] The second embodiment of the present disclosure provides a target object information statistics device, which avoids the interference of environmental factors on target object identification and improves the efficiency and accuracy of target object information statistics.

[0079] Furthermore, the target object information determination module 230 further includes:

[0080] an electrical signal determining unit, configured to determine an electrical signal based on the local oscillator optical signal and the echo signal;

[0081] The first determining unit is configured to determine target object information corresponding to the target object based on the frequency of the electrical signal.

[0082] Furthermore, the electrical signal determination unit is further configured to:

[0083] Using an optical mixer to superimpose the local oscillator light signal and the echo signal to obtain an interference light signal, wherein the interference light signal carries the frequency difference between the local oscillator light signal and the echo signal corresponding to the target object;

[0084] The interference light signal is converted into the electrical signal by using a photodetector.

[0085] Furthermore, the device further comprises:

[0086] a moving target determination module, configured to determine at least two moving targets based on a moving speed of each target relative to the FMCW lidar and a preset speed threshold when the target scene contains multiple targets;

[0087] The inflow and outflow flow determination module is used to determine the inflow and outflow flow of the target scene based on the installation position of the FMCW laser radar and the frequency difference corresponding to each of the moving targets.

[0088] Furthermore, the inflow and outflow determination module further includes:

[0089] a motion direction determining unit, configured to determine a motion direction of each of the moving targets based on an installation position of the FMCW laser radar and a frequency difference corresponding to each of the moving targets;

[0090] The second determining unit is configured to determine the inflow and outflow flow of the target scene based on the moving direction of each moving target object.

[0091] Furthermore, the second determining unit is further configured to:

[0092] Determining a first moving target set and a second moving target set based on the moving direction of each of the moving targets, wherein the moving directions of the moving targets in the first target set and the second target set are opposite;

[0093] The inflow and outflow traffic of the target scene is determined based on the first target object set and the second target object set.

[0094] The target object information statistics device provided in the embodiments of the present disclosure can execute the target object information statistics method provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Example 3

[0096] Figure 5 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are provided for example only and are not intended to limit the implementation of the embodiments of the present disclosure described and / or claimed herein.

[0097] like Figure 5As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0098] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0099] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors that run machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microprocessor, etc. The processor 11 executes the various methods and processes described above, such as the target object information statistical method.

[0100] In some embodiments, the target object information statistics method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the target object information statistics method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the target object information statistics method in any other appropriate manner (for example, by means of firmware).

[0101] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0102] The computer programs for implementing the methods of the embodiments of the present disclosure may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0103] In the context of the embodiments of the present disclosure, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0104] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0105] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0106] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0107] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the embodiments of the present disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of the embodiments of the present disclosure can be achieved, and this document is not limited here.

[0108] The above specific implementations do not constitute a limitation on the scope of protection of the embodiments of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the embodiments of the present disclosure shall be included within the scope of protection of the embodiments of the present disclosure.

[0109] The embodiments of the present disclosure also provide a computer program product, including a computer program and / or instructions, which, when executed by a processor, implements the target object information statistics method provided in any embodiment of the present application.

[0110] During implementation, the computer program product may be written in one or more programming languages ​​or a combination thereof to write computer program code for performing the operations of the disclosed embodiments, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0111] Note that the above are only preferred embodiments of the present disclosure and the technical principles used. Those skilled in the art will understand that the present disclosure is not limited to the specific embodiments herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present disclosure. Therefore, although the present disclosure is described in more detail through the above embodiments, the present disclosure is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present disclosure, and the scope of the present disclosure is determined by the scope of the appended claims.

Claims

1. A method for statistically analyzing target information, characterized in that: include: A beam splitter is used to separate the modulated optical signal into a transmitted optical signal and a local oscillator optical signal; The frequency of the modulated optical signal is a linear triangular wave; Directing the emitted light signal toward a target object in a target scene to determine an echo signal corresponding to the target object; The target object information corresponding to the target object is determined based on the local oscillator light signal and the echo signal; the target object information includes the moving speed of the target object relative to the FMCW laser radar and the distance between the target object and the FMCW laser radar.

2. The method according to claim 1, characterized in that The determining target information corresponding to the target based on the local oscillator light signal and the echo signal includes: determining an electrical signal based on the local oscillator optical signal and the echo signal; Target object information corresponding to the target object is determined based on the frequency of the electrical signal.

3. The method according to claim 2, characterized in that The determining of the electrical signal based on the local oscillator optical signal and the echo signal includes: Using an optical mixer to superimpose the local oscillator light signal and the echo signal to obtain an interference light signal, wherein the interference light signal carries the frequency difference between the local oscillator light signal and the echo signal corresponding to the target object; The interference light signal is converted into the electrical signal by using a photodetector.

4. The method according to claim 1, wherein The method further comprises: In a case where the target scene includes multiple targets, determining at least two moving targets based on the movement speed of each target relative to the FMCW laser radar and a preset speed threshold; The inflow and outflow traffic of the target scene is determined based on the installation position of the FMCW laser radar and the frequency difference corresponding to each of the moving targets.

5. The method according to claim 4, characterized in that The determining of the inflow and outflow of the target scene based on the installation position of the FMCW laser radar and the frequency difference corresponding to each of the moving targets includes: Determining the movement direction of each of the moving targets based on the installation position of the FMCW laser radar and the frequency difference corresponding to each of the moving targets; The inflow and outflow traffic of the target scene is determined based on the movement direction of each of the moving targets.

6. The method according to claim 5, characterized in that The determining of the inflow and outflow flow of the target scene based on the movement directions respectively corresponding to the moving targets includes: Determining a first moving target set and a second moving target set based on the moving direction of each of the moving targets, wherein the moving directions of the moving targets in the first target set and the second target set are opposite; The inflow and outflow traffic of the target scene is determined based on the first target object set and the second target object set.

7. A target object information statistics device, characterized in that: include: A light splitting module, used to use a beam splitter to split the modulated light signal into a transmitted light signal and a local oscillator light signal; The frequency of the modulated optical signal is a linear triangular wave; an echo signal determination module, configured to direct the emitted light signal toward a target object in a target scene to determine an echo signal corresponding to the target object; A target information determination module is used to determine target information corresponding to the target based on the local oscillator light signal and the echo signal; the target information includes the moving speed of the target relative to the FMCW laser radar and the distance between the target and the FMCW laser radar.

8. An electronic device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the target object information statistics method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the target object information statistics method as described in any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the target object information statistics method according to any one of claims 1 to 6 is implemented.

Images