Lidar-based object detection method, apparatus, processor, and storage medium

Abstract

This invention provides a method, apparatus, processor, and storage medium for object detection based on lidar. The method further includes: transmitting signal light emitted by a laser to a target object via optical devices and an optical phased array transceiver; detecting end-face reflection signals and target reflection signals, wherein the end-face reflection signal is formed by reflection from the optical phased array transceiver and optical devices, and the target reflection signal is formed by reflection from the target object; determining the spectral distance between the end-face reflection frequency and the target reflection frequency based on the end-face reflection signal and the target reflection signal; adjusting the spectral distance if it is less than a distance threshold; determining the passband frequency and stopband frequency of a filter based on the adjusted spectral distance; filtering out the end-face reflection signal from the target reflection signal according to the passband frequency and stopband frequency; and detecting the position of the target object based on the filtered target reflection signal. This invention solves the technical problem of inaccurate target object position information detection.

Description

Technical Field

[0001] The present invention relates to the field of lidar technology, and more specifically, to a lidar-based object detection method, apparatus, processor, and storage medium. Background Technology

[0002] Currently, in frequency-modulated continuous wave lidar, the optical phased array (OPA) transceiver system is used for laser transmission and reception. However, in the OPA transceiver system, each coupled end face may generate a reflection signal (end face reflection signal). Based on this, when the laser signal emitted by the frequency-modulated continuous wave lidar is transmitted to the target object through the optical phased array transceiver, the optical phased array transceiver will generate an end face reflection signal after receiving the laser. The delay time of this end face reflection signal is very close to that of the target reflection signal generated by the target object. This causes the frequency point generated by the end face reflection signal in the receiving circuit to overlap or be very close to the frequency point generated by the target reflection signal. As a result, during the signal processing stage, the end face reflection frequency point and the target reflection frequency point are too close, making it difficult for the system to effectively distinguish between the two. Especially when the target reflection frequency point is close to the end face reflection frequency point, it may cause the target signal to be missed, that is, the target cannot be correctly identified, or a close-range measurement blind zone may be generated, that is, the target information cannot be accurately measured within a certain distance range, thus making it impossible to accurately detect the position information of the target object based on the target reflection signal.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a method, apparatus, processor, and storage medium for object detection based on lidar, to at least solve the technical problem of inaccurate detection of target object location information.

[0005] According to an embodiment of the present invention, object detection based on lidar is provided, comprising: responding to a signal light emitted by a laser being transmitted to a target object via an optical device and an optical phased array transceiver; detecting an end-face reflection signal and a target reflection signal, wherein the end-face reflection signal is formed by reflection from the optical phased array transceiver and the optical device, and the target reflection signal is formed by reflection from the target object; determining the spectral distance between the end-face reflection frequency point and the target reflection frequency point in the spectrum based on the end-face reflection signal and the target reflection signal; adjusting the spectral distance in response to the spectral distance being less than a distance threshold; determining the passband frequency and stopband frequency of a filter based on the adjusted spectral distance, wherein the passband frequency is used to represent the frequency range of signals allowed by the filter, and the stopband frequency is used to represent the frequency range of signals prohibited by the filter; controlling the filter to filter out the end-face reflection signal from the target reflection signal according to the passband frequency and the stopband frequency; and detecting the position of the target object based on the filtered target reflection signal.

[0006] In an exemplary embodiment, determining the spectral distance between the end-face reflection frequency point and the target reflection frequency point in the spectrum based on the end-face reflection signal and the target reflection signal includes: mixing the end-face reflection signal with the local oscillator signal of the laser to generate a first difference frequency signal corresponding to the end-face reflection signal, and mixing the target reflection signal with the local oscillator signal to generate a second difference frequency signal corresponding to the target reflection signal, wherein the local oscillator signal is a reference signal emitted by the laser with the same frequency as the signal light; and determining the spectral distance based on the first difference frequency signal and the second difference frequency signal.

[0007] In an exemplary embodiment, determining the spectral distance based on a first difference frequency signal and a second difference frequency signal includes: converting the first difference frequency signal into a first digital signal and the second difference frequency signal into a second digital signal using an analog-to-digital converter; performing a Fourier transform on the first digital signal to obtain the end-face reflection frequency point and performing a Fourier transform on the second digital signal to obtain the target reflection frequency point; and determining the spectral distance based on the position of the end-face reflection frequency point in the spectrum and the position of the target reflection signal in the spectrum.

[0008] In an exemplary embodiment, the end-face reflection frequency is associated with the optical path difference between the end-face reflection position of the optical phased array transceiver and the local oscillator position of the laser. The optical path difference is associated with the fiber length between the end-face reflection position and the local oscillator position. Adjusting the spectral distance includes: determining a target fiber length between the end-face reflection position of the optical phased array transceiver and the local oscillator position of the laser, wherein the target fiber length is used to represent the fiber length that makes the spectral distance between the end-face reflection frequency and the target reflection frequency satisfy a distance threshold; and adjusting the current fiber length between the end-face reflection position and the local oscillator position to the target fiber length to adjust the spectral distance between the end-face reflection frequency and the target reflection frequency.

[0009] In one exemplary embodiment, the spectral distance between the adjusted end-face reflection frequency and the target reflection frequency is greater than a distance threshold.

[0010] In one exemplary embodiment, determining the passband frequency and stopband frequency of a filter based on the adjusted spectral distance includes: determining the passband frequency and stopband frequency of the filter based on the adjusted spectral distance; determining the adjusted end-face reflection frequency and the adjusted target reflection frequency; and determining the passband frequency and stopband frequency of the filter based on the adjusted end-face reflection frequency and the adjusted target reflection frequency.

[0011] In one exemplary embodiment, the passband frequency of the filter covers the target reflection frequency, and the stopband frequency of the filter covers the end-face reflection frequency.

[0012] In one exemplary embodiment, the filter is at least a high-pass filter or a notch filter.

[0013] According to another embodiment of the present invention, a lidar-based object detection device is provided, comprising: a first detection unit, configured to detect end-face reflection signals and target reflection signals in response to signal light emitted by a laser being transmitted to a target object through optical devices and an optical phased array transceiver, wherein the end-face reflection signal is formed by reflection from the optical phased array transceiver and the optical devices, and the target reflection signal is formed by reflection from the target object; a first determination unit, configured to determine the spectral distance between the end-face reflection frequency point and the target reflection frequency point in the spectrum based on the end-face reflection signal and the target reflection signal; an adjustment unit, configured to adjust the spectral distance in response to the spectral distance being less than a distance threshold; a second determination unit, configured to determine the passband frequency and stopband frequency of a filter based on the adjusted spectral distance, wherein the passband frequency is used to represent the frequency range of signals allowed by the filter, and the stopband frequency is used to represent the frequency range of signals prohibited by the filter; a filtering unit, configured to control the filter to filter out the end-face reflection signal in the target reflection signal according to the passband frequency and the stopband frequency; and a second detection unit, configured to detect the position of the target object based on the filtered target reflection signal.

[0014] According to yet another embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium storing a plurality of instructions adapted for loading by a processor and executing the steps in any of the above method embodiments.

[0015] According to yet another embodiment of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0016] According to yet another embodiment of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0017] This invention addresses the issue that when the spectral distance between the end-face reflection frequency and the target reflection frequency is small, it allows for adjustment to ensure sufficient spacing between them and prevent frequency overlap. Subsequently, based on the adjusted end-face and target reflection frequencies, the passband and stopband frequencies of the filter are determined. This ensures the filter effectively filters out the end-face reflection signal while remaining unaffected by the target reflection signal, effectively extracting the target reflection signal from the received signal. The extracted target reflection signal then accurately calculates the target object's position, improving the accuracy of target object position detection and solving the technical problem in related technologies where inaccurate target object position detection is caused by the difficulty in distinguishing between target and end-face reflection signals. Attached Figure Description

[0018] Figure 1 This is a hardware structure block diagram of a mobile terminal based on a lidar-based object detection method according to an embodiment of the present invention.

[0019] Figure 2 This is a flowchart of an object detection method based on lidar according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of the spectral distance between an end-face reflection frequency point and a target reflection frequency point according to an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of the spectral distance between the adjusted end-face reflection frequency and the target reflection frequency according to an embodiment of the present invention;

[0022] Figure 5 This is an output waveform diagram of an ADC according to an embodiment of the present invention;

[0023] Figure 6 This is a schematic diagram of a lidar system according to an embodiment of the present invention;

[0024] Figure 7 This is a schematic diagram illustrating the difference in frequency response characteristics between an ideal filter and a practical filter according to an embodiment of the present invention.

[0025] Figure 8 This is a comparative schematic diagram of multiple end-face reflection frequency points before and after changing the optical path difference according to an embodiment of the present invention;

[0026] Figure 9 This is a comparison diagram of the frequency response of a practically designed filter and an ideal filter according to an embodiment of the present invention;

[0027] Figure 10 This is a structural block diagram of an object detection device based on lidar according to an embodiment of the present invention;

[0028] Figure 11 This is a schematic diagram of the structure of an electronic device for a lidar-based object detection method according to an embodiment of the present invention. Detailed Implementation

[0029] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0031] The methods and embodiments provided in this invention can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for an object detection method based on LiDAR according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0032] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the lidar-based object detection method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0033] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0034] Those skilled in the art will understand that Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0035] In one possible implementation, embodiments of this disclosure provide a lidar-based object detection method. Figure 2 This is a flowchart of an object detection method based on lidar according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0036] In step S201, in response to the signal light emitted by the laser being transmitted to the target object through optical devices and an optical phased array transceiver, the end face reflection signal and the target reflection signal are detected.

[0037] In the technical solution provided in step S201 of the present invention, the end-face reflection signal is formed by reflection from the optical phased array transceiver and optical devices, and the target reflection signal is formed by reflection from the target object. The laser can be a frequency-modulated continuous wave lidar, which is a sensor that uses the interference of transmitted and received laser information to calculate the position, velocity, and other characteristics of the detected target. The optical devices include various lenses and mirrors used to guide and focus the laser signal (signal light), ensuring accurate transmission of the laser signal. The optical phased array transceiver (OPA transceiver) contains multiple coupling end faces, which couple the laser signal in the optical path. After receiving the laser signal (signal light), both the optical devices and the OPA transceiver reflect a portion of the laser signal; this reflected portion is called the end-face reflection signal.

[0038] In this embodiment, when the laser is operating, the signal light emitted by the laser is transmitted to an optical phased array (OPA) transceiver through optical components. After receiving the signal light, the OPA transceiver can emit a portion of the signal light towards the target object and reflect the other portion. The target object, after receiving the signal light, can also reflect it, generating a target reflection signal. That is, the end-face reflection signal and the target reflection signal have different paths within the OPA transceiver. The end-face reflection signal is directly reflected inside the transceiver and returns to the receiving path, while the target reflection signal must travel the complete optical path from emission from the OPA transceiver, to reflection from the target object, and then back to reception by the OPA transceiver.

[0039] Optionally, after the signal light reaches the target object via the OPA transceiver, it is reflected back to the lidar system by the target. During this process, the reflected signal contains information such as the target object's position and velocity, which is crucial for the system's detection and identification of the target object. However, since the end-face reflection signal and the target reflection signal return to the receiving circuit almost simultaneously, the frequency points of the signals generated at the receiving end may be very close. Especially when the end-face reflection signal intensity is high, such frequency overlap can cause serious interference to signal processing.

[0040] Optionally, the aliasing of the end-face reflection signal and the target reflection signal may not only saturate the amplifier and analog-to-digital converter (ADC) in the receiving circuit, affecting the accurate acquisition and processing of subsequent signals, but also make it difficult for the signal processing algorithm to identify the target reflection signal. In particular, when the target reflection frequency is too close to the end-face reflection frequency, it may lead to the failure to identify the target reflection signal, forming a blind zone for close-range measurement and affecting the accurate detection of the target object's position information by the lidar. Based on this, after determining the end-face reflection signal and the target reflection signal, the spectral distance between the end-face reflection frequency and the target reflection frequency can be further determined through the following step S202.

[0041] Step S202: Based on the end face reflection signal and the target reflection signal, determine the spectral distance between the end face reflection frequency point and the target reflection frequency point in the spectrum.

[0042] In the technical solution provided in step S202 of the present invention, the end-face reflection frequency point is used to indicate the position of the frequency generated by the interference between the end-face reflection signal and the local oscillator light emitted by the laser in the frequency spectrum. The target reflection frequency point is used to indicate the position of the frequency generated by the interference between the target reflection signal and the local oscillator light of the laser in the frequency spectrum. The local oscillator light is used to indicate a reference signal emitted by the laser that matches the modulation frequency of the signal light. For example, when the laser emits signal light, a portion of the same laser signal is separated and directly sent to the receiving end; this portion of the signal is the local oscillator light. The local oscillator light can perform optical interference with the signal light reflected back from the outside at the receiving end. The spectral distance between the end-face reflection frequency point and the target reflection frequency point in the frequency spectrum refers to the size of the interval between these two frequency points on the frequency axis.

[0043] In this embodiment, both the end-face reflection signal and the target reflection signal are processed through the same receiving circuit after returning to the lidar. In the receiving circuit, the end-face reflection signal is mixed with the local oscillator light to generate an end-face reflection frequency, and the target reflection signal is mixed with the local oscillator light to generate a target reflection frequency.

[0044] Optionally, both the end-face reflection frequency and the target reflection frequency are determined by factors such as the optical path difference, the modulation bandwidth of the laser, and the modulation period. For example, the following formula (1) is the formula for calculating the end-face reflection frequency.

[0045]

[0046] Where f is the end-face reflection frequency, B is the laser modulation bandwidth, ΔR is the optical path difference between the end-face reflection position and the local oscillator position, c is the speed of light, and T is the modulation period. As can be seen from the above formula, the end-face reflection frequency is determined by the optical path difference between the reflection position and the local oscillator position, the modulation bandwidth, and the modulation period.

[0047] Optionally, after determining the end-face reflection frequency and the target reflection frequency, the distance between the two can be determined based on the position information of the end-face reflection frequency and the position information of the target reflection frequency in the spectrum, and then this distance can be determined as the spectral distance between the end-face reflection frequency and the target reflection frequency in the spectrum.

[0048] Step S203: In response to the spectral distance being less than the distance threshold, adjust the spectral distance.

[0049] In the technical solution provided by step S203 of the present invention, after determining the spectral distance between the end face reflection frequency point and the target reflection frequency point through step S202, the spectral distance can be compared with a distance threshold, and then the spectral distance between the two can be adjusted according to the comparison result.

[0050] In this embodiment, if the spectral distance between the target reflection frequency and the end face reflection frequency is too small, i.e. the frequency difference is insufficient, the signal processing algorithm may be unable to accurately distinguish between the two signals, thereby affecting the identification and measurement of the target.

[0051] For example, Figure 3 This is a schematic diagram of the spectral distance between the end-face reflection frequency point and the target reflection frequency point according to an embodiment of the present invention, as shown below. Figure 3 As shown, when the target signal frequency is very close to the end face reflection frequency, the system may mistake the end face reflection signal for the target signal, resulting in missed identification or blind spots in close-range measurement.

[0052] Optionally, when the spectral distance between the target reflected signal and the end face reflected signal is less than a preset distance threshold, the spectral distance can be adjusted. For example, the spectral distance can be adjusted by adjusting the position of the end face reflection frequency point in the spectrum.

[0053] Optionally, as described above, the end-face reflection frequency is determined by the optical path difference, modulation bandwidth, and modulation period between the reflection position and the local oscillator position. Based on this, the position of the end-face reflection frequency in the spectrum can be moved by adjusting the fiber length or delay between the end-face reflection signal and the local oscillator signal, so that the end-face reflection signal can be clearly placed in a frequency band that does not overlap with the target signal frequency.

[0054] Optionally, Figure 4 This is a schematic diagram of the spectral distance between the adjusted end-face reflection frequency and the target reflection frequency according to an embodiment of the present invention, as shown below. Figure 4 As shown, the distance between the position of the end face reflection frequency point and the position of the target reflection frequency point is increased after the adjustment, thus avoiding the problem of frequency point overlap.

[0055] Optionally, after adjusting the position of the end-face reflection frequency point, the spectral distance between the end-face reflection frequency point and the target reflection frequency point can be recalculated. If the spectral distance is greater than the distance threshold, step S204 is executed. Conversely, if the spectral distance between the two is not greater than the distance threshold, the spectral distance between the two can continue to be adjusted according to the above method until the spectral distance is greater than the distance threshold.

[0056] In this step, by adjusting the spectral distance between the end-face reflection frequency and the target reflection frequency, it is possible to ensure that the target signal and the end-face reflection signal are clearly distinguishable in the spectrum, avoiding problems such as signal saturation, missed identification, and blind spots in close-range measurement, and significantly improving the system's performance in signal processing and target detection.

[0057] Step S204: Determine the passband frequency and stopband frequency of the filter based on the adjusted spectral distance.

[0058] In the technical solution provided in step S204 of the present invention, the passband frequency is used to represent the frequency range of signals that the filter allows to pass through, and the stopband frequency is used to represent the frequency range of signals that the filter prohibits to pass through.

[0059] In this embodiment, since it is difficult to design a filter that can effectively distinguish between the end-face reflection signal and the target reflection signal when their frequency points are too close, the spectral distance between the end-face reflection frequency point and the target reflection frequency point is adjusted through the above step S203. Then, the passband frequency and stopband frequency of the filter can be determined according to the adjusted spectral distance so that the filter can effectively suppress the end-face reflection signal while ensuring the integrity of the target signal.

[0060] For example, the passband frequency can be set according to the frequency range corresponding to the target reflected signal on the spectrum, ensuring that all signals containing target information can pass through the filter without attenuation and be processed by subsequent circuits and algorithms to achieve accurate detection and positioning of the target.

[0061] Optionally, the stop band frequency can be set according to the frequency range corresponding to the end face reflection signal on the spectrum. The stop band frequency can be set within the frequency range of the end face reflection signal so that the end face reflection signal can be completely filtered out through the suppression effect of the filter, thus avoiding its influence on the correct identification and processing of the target reflection signal.

[0062] Optionally, by adjusting the spectral distance between the end-face reflection frequency and the target reflection frequency, even with a low-order, simple filter design, effective suppression of the end-face reflection signal can be achieved, while ensuring the integrity of the target signal and accurate target identification by the system. In this way, the lidar system can not only avoid signal saturation and missed identification problems, but also reduce blind spots in close-range measurements, improve overall ranging capability and signal processing efficiency, ultimately achieving higher system performance and application flexibility.

[0063] Step S205: Control the filter to filter out end-face reflection signals in the target reflection signal according to the passband frequency and stopband frequency.

[0064] In the technical solution provided by step S205 of the present invention, after the passband frequency and stopband frequency of the filter are determined by step S204, the filter can be controlled to filter out the end face reflection signal in the target reflection signal according to the passband frequency and stopband frequency, so as to eliminate or significantly reduce the interference of the end face reflection signal on the target reflection signal.

[0065] Optionally, the passband frequency and stopband frequency determined above are used to configure the passband frequency and stopband frequency of the filter, and the filter is placed before the amplifier and ADC at the receiving end of the lidar system, so that the end-face reflection signal reflected by the OPA transceiver can be filtered out when it passes through the filter set in the receiving circuit, and the target reflection signal reflected by the target object can pass through the filter completely, and then be amplified by the amplifier and converted by the ADC.

[0066] Optionally, after filtering, the end-face reflection component of the target reflection signal is significantly reduced, and the signal processing algorithm can more clearly and accurately identify and extract the frequency information in the target reflection signal for subsequent determination of the target object's position information.

[0067] Optionally, in a lidar system, the end-face reflection signal, due to its inherent frequency characteristics, may be too close to the target reflection signal in the spectrum, leading to difficulties in signal identification and processing. By designing and applying filters, especially high-pass or band-stop filters, signals within specific frequency bands can be filtered out, thereby effectively suppressing the end-face reflection signal and retaining useful information in the target reflection signal.

[0068] In this step, by setting the passband frequency and stopband frequency of the filter, the end-face reflection signal component in the target reflection signal can be effectively filtered out, thereby optimizing the signal quality and improving the target recognition and measurement performance of the lidar system.

[0069] Step S206: Detect the position of the target object based on the filtered target reflection signal.

[0070] In the technical solution provided in step S206 of the present invention, the filtered target reflection signal is subjected to signal analysis methods such as Fourier transform to extract frequency information from the signal. This frequency information corresponds to the Doppler frequency shift of the target reflection signal, reflecting the relative speed and distance of the target object relative to the lidar. Therefore, based on this relative speed and distance, the position information of the target object can be determined.

[0071] Through steps S201 to S206, when the spectral distance between the end-face reflection frequency point and the target reflection frequency point is small, the spectral distance can be adjusted to ensure sufficient spacing between them and avoid frequency overlap. Then, based on the adjusted end-face reflection frequency point and target reflection frequency point, the passband frequency and stopband frequency of the filter are determined to ensure that the filter effectively filters out the end-face reflection signal while ensuring that the target reflection signal is unaffected. This achieves the goal of effectively extracting the target reflection signal from the received signal, and then accurately calculating the position of the target object based on the extracted target reflection signal. This improves the accuracy of target object position information detection and solves the technical problem in related technologies where the inaccurate detection of target object position information is caused by the difficulty in distinguishing between target reflection signals and end-face reflection signals.

[0072] The embodiments of the present invention will now be described in detail with reference to the steps described above.

[0073] As an optional embodiment, step S202, determining the spectral distance between the end-face reflection frequency point and the target reflection frequency point based on the end-face reflection signal and the target reflection signal, includes: mixing the end-face reflection signal with the local oscillator signal of the laser to generate a first difference frequency signal corresponding to the end-face reflection signal, and mixing the target reflection signal with the local oscillator signal to generate a second difference frequency signal corresponding to the target reflection signal, wherein the local oscillator signal is a reference signal emitted by the laser with the same frequency as the signal light; and determining the spectral distance based on the first difference frequency signal and the second difference frequency signal.

[0074] In this embodiment, as described above, in a frequency-modulated continuous wave lidar system, the signal light emitted from the laser is reflected at the coupling end face within the OPA transceiver system, forming an end face reflection signal; the other part of the signal light reaches the target object and is reflected, forming a target reflection signal. The local oscillator signal is a reference signal with the same or similar frequency as the signal light emitted by the laser, and is usually separated from the signal light emitted by the laser using beam splitting technology. Frequency mixing is the process of combining the received signal (end face reflection signal or target reflection signal) with the local oscillator signal in terms of frequency.

[0075] Optionally, the first difference frequency signal generated after the end face reflection signal and the local oscillator signal are mixed reflects the relative frequency difference between the end face reflection signal and the local oscillator signal. This frequency difference is determined by the optical path difference of the end face reflection signal. According to the aforementioned formula (1), the end face reflection frequency is determined by the modulation bandwidth, the optical path difference between the reflection position and the local oscillator position, the speed of light, and the modulation period. The frequency of the first difference frequency signal is the frequency characteristic of the end face reflection signal.

[0076] Optionally, the second difference frequency signal generated after mixing the target reflected signal with the local oscillator signal also reflects a relative frequency difference, which is determined by the optical path difference of the target reflected signal. This optical path difference is determined by the time required for the signal light to reach the target and be reflected back. The frequency characteristics of the target reflection frequency point are reflected through the second difference frequency signal, which carries the position and velocity information of the target object.

[0077] Optionally, the spectral distance is used to indicate the frequency interval between the end-face reflection frequency and the target reflection frequency in the frequency domain. The spectral distance between the end-face reflection frequency and the target reflection frequency can be calculated by comparing the frequencies of the first difference frequency signal and the second difference frequency signal. If the spectral distance is too small, the end-face reflection frequency and the target reflection frequency may overlap in frequency, causing the signal processing algorithm to be unable to correctly distinguish between them, resulting in problems such as signal saturation, missed identification, and blind spots in close-range measurements.

[0078] As an optional embodiment, determining the spectral distance based on the first difference frequency signal and the second difference frequency signal includes: converting the first difference frequency signal into a first digital signal and the second difference frequency signal into a second digital signal using an analog-to-digital converter; performing a Fourier transform on the first digital signal to obtain the end-face reflection frequency point and performing a Fourier transform on the second digital signal to obtain the target reflection frequency point; and determining the spectral distance based on the position of the end-face reflection frequency point in the spectrum and the position of the target reflection signal in the spectrum.

[0079] In this embodiment, the purpose of signal difference frequency processing, analog-to-digital conversion, and spectrum analysis in the frequency modulated continuous wave lidar system is to accurately determine the spectral distance between the end face reflection signal and the target reflection signal, providing the necessary data foundation for filter design and signal processing.

[0080] Optionally, after the lidar system emits signal light, a portion of the signal light is reflected back at the coupling facet of the OPA transceiver, forming a facet reflection signal; the other portion of the signal light continues to propagate, interacts with the target object, and is reflected back, forming a target reflection signal. At the receiving end, these two signals are mixed with the local oscillator light to generate a first difference frequency signal (corresponding to the facet reflection signal) and a second difference frequency signal (corresponding to the target reflection signal), respectively. The frequency of the difference frequency signal is directly related to the optical path difference between the emitted and received light, and thus to the facet reflection position and the target distance.

[0081] Optionally, in order to perform digital signal processing on these signals, the first difference frequency signal and the second difference frequency signal need to be converted into digital signals. For example, an analog-to-digital converter (ADC) can be used to convert the first difference frequency signal and the second difference frequency signal. The ADC receives the analog signals (the first difference frequency signal and the second difference frequency signal) and converts them into digital signals (the first digital signal and the second digital signal) to facilitate subsequent digital signal processing algorithms, such as Fourier transform.

[0082] Optionally, after obtaining the first and second digital signals, Fourier transforms can be performed on them. Fourier transforms convert the time-domain digital signal to the frequency domain, revealing the frequency components of the signal. Performing Fourier transforms on the first digital signal (from end-face reflection) and the second digital signal (from target reflection) respectively yields the end-face reflection frequency and the target reflection frequency. The end-face reflection frequency is generated by mixing the end-face reflection signal with the local oscillator light, while the target reflection frequency is obtained by mixing the target reflection signal with the local oscillator light, reflecting the target's relative position and motion state.

[0083] Optionally, after determining the end-face reflection frequency and the target reflection frequency, the distance between the two positions on the spectrum provides a direct quantitative indicator of the frequency difference between the end-face reflection signal and the target reflection signal, i.e., the spectral distance.

[0084] As an optional embodiment, the end-face reflection frequency point is associated with the optical path difference between the end-face reflection position of the optical phased array transceiver and the local oscillator position of the laser. The optical path difference is associated with the fiber length between the end-face reflection position and the local oscillator position. Step S203, adjusting the spectral distance, includes: determining the target fiber length between the end-face reflection position of the optical phased array transceiver and the local oscillator position of the laser, wherein the target fiber length is used to represent the fiber length that makes the spectral distance between the end-face reflection frequency point and the target reflection frequency point meet the distance threshold; adjusting the current fiber length between the end-face reflection position and the local oscillator position to the target fiber length to adjust the spectral distance between the end-face reflection frequency point and the target reflection frequency point.

[0085] In this embodiment, the target fiber length is a key parameter ensuring that the spectral distance between the end-face reflection frequency and the target reflection frequency meets a specific "distance threshold." This distance threshold is essentially a frequency difference threshold, referring to the minimum frequency difference in the spectrum that the signal processing algorithm must achieve to effectively distinguish between the end-face reflected signal and the target reflected signal. Determining the target fiber length involves calculating and adjusting the optical path difference to ensure that the frequency difference between the end-face reflection frequency and the target reflection frequency is large enough to meet the requirements of signal processing.

[0086] For example, the optical path difference, which is the difference in the actual propagation path length between the signal light at the end-face reflection position and the local oscillator position, is directly related to the fiber length. For instance, by increasing or decreasing the fiber length between the end-face reflection position and the local oscillator position, the optical path difference can be changed, thereby changing the position of the end-face reflected signal in the spectrum, i.e., the end-face reflection frequency. The change in the optical path difference will affect the calculation of the end-face reflection frequency in formula (1), thus affecting the actual value of the end-face reflection frequency.

[0087] Optionally, after determining the target fiber length, the current fiber length needs to be adjusted to this target value. This is typically achieved by increasing or decreasing the physical length of the fiber between the end-face reflection position and the local oscillator position. For example, if the current fiber length is less than the target fiber length, the physical length of the fiber between the end-face reflection position and the local oscillator position needs to be increased, thereby increasing the optical path difference between the end-face reflection position and the local oscillator position, thus moving the end-face reflection frequency away from the target reflection frequency.

[0088] Optionally, when the spectral distance between the end-face reflection frequency and the target reflection frequency is adjusted to a sufficiently large value, it can be ensured that the filter can effectively filter out the end-face reflection signal, while the target reflection signal can pass through without interference. In this way, even with a simple filter design, the system can maintain good performance and avoid problems such as signal saturation, missed identification, and blind spots in close-range measurements.

[0089] As an optional embodiment, the spectral distance between the adjusted end-face reflection frequency and the target reflection frequency is greater than a distance threshold.

[0090] In this embodiment, the distance threshold is a critical value set according to system performance requirements and filter design capabilities. It is used to ensure that the spectral distance between the end-face reflection frequency point and the target reflection frequency point is large enough so that the end-face reflection signal can be effectively separated and suppressed by the filter. The adjusted spectral distance between the end-face reflection frequency point and the target reflection frequency point is greater than the distance threshold. By designing the passband frequency and stopband frequency of the filter, the filter can effectively filter out the end-face reflection signal in the target reflection signal, thereby maintaining the integrity of the target reflection signal.

[0091] As an optional embodiment, step S204, determining the passband frequency and stopband frequency of the filter based on the adjusted spectral distance, includes: determining the passband frequency and stopband frequency of the filter based on the adjusted spectral distance, determining the adjusted end-face reflection frequency and the adjusted target reflection frequency; and determining the passband frequency and stopband frequency of the filter based on the adjusted end-face reflection frequency and the adjusted target reflection frequency.

[0092] In this embodiment, determining the passband frequency and stopband frequency of the filter based on the adjusted spectral distance is a key step to ensure that the system can effectively extract the target reflected signal while suppressing interference from the end face reflected signal.

[0093] Optionally, the passband frequency should cover the frequency range of the target reflection points to ensure that the target reflection signal can pass through the filter without attenuation, thereby being accurately detected and analyzed by the system. The passband setting needs to take into account the distribution range of the target reflection points and possible Doppler frequency shift to ensure signal integrity and measurement accuracy.

[0094] Optionally, the stopband frequency should cover the frequency range of the adjusted end-face reflection frequency point to suppress the end-face reflection signal. By placing the end-face reflection frequency point within the stopband of the filter, its influence can be effectively attenuated or eliminated, avoiding problems such as signal saturation and blind spots in close-range measurements, and ensuring the clarity and identifiability of the target reflection signal.

[0095] Optionally, based on the adjusted spectral distance, the frequency response characteristics of the filter are designed, i.e., the specific frequency ranges of its passband and stopband are determined. The passband is designed to allow the target reflected signal to pass through, while the stopband is designed to filter out the end-face reflected signal, ensuring the accuracy of signal processing.

[0096] Optionally, when designing a filter, its performance parameters, such as passband gain, passband flatness, and stopband attenuation rate, also need to be considered. By adjusting the filter's structure (such as filter order, zero and pole positions, etc.), its performance in the passband and stopband can be optimized, effectively filtering out end-face reflected signals while minimizing the impact on the target signal.

[0097] In this step, the adjusted spectral distance provides key parameters for filter design, enabling even simple filters to meet system performance requirements, reducing the difficulty of system design, and improving the stability and measurement accuracy of lidar in complex environments.

[0098] As an optional embodiment, the passband frequency of the filter covers the target reflection frequency, and the stopband frequency of the filter covers the end-face reflection frequency.

[0099] In this embodiment, as described above, the passband frequency refers to the frequency range that the filter allows signals to pass through. Within this range, the signal amplitude changes little, meaning the filter does not significantly attenuate the signal. In a lidar system, the frequency of the target reflection signal carries the target's position and velocity information. Therefore, the filter's passband frequency design should cover the target reflection frequency to ensure that these signals carrying target information can pass through the filter without loss or with low loss, providing high-quality input for subsequent signal processing and data decoding.

[0100] Optionally, as described above, the stopband frequency is the frequency range of the signal suppressed by the filter. Within this range, the filter will significantly attenuate or completely suppress the signal to eliminate unwanted frequency components. Due to the unique characteristics of end-face reflection signals generated within the system, they may cause problems such as signal saturation, missed identification, and blind zones, affecting the accurate detection and calculation of target reflection signals. Therefore, the stopband frequency design of the filter should cover the end-face reflection frequency points to ensure that these interference signals are effectively filtered out and their impact on target signal processing is reduced.

[0101] Optionally, by making the filter's passband cover the target reflection frequency and the filter's stopband frequency cover the end face reflection frequency, it can be ensured that the target reflection frequency is covered within the passband and the end face reflection frequency is placed within the stopband. This can effectively improve system performance, increase measurement accuracy and stability, and thus achieve more reliable target detection and positioning in various application scenarios.

[0102] As an optional embodiment, the filter is at least a high-pass filter or a notch filter.

[0103] In this embodiment, the high-pass filter allows high-frequency signals to pass through while reducing or blocking the passage of low-frequency signals. In lidar signal processing, high-pass filters are mainly used to suppress low-frequency end-face reflection signals, as these signals are often generated by reflections within the optical fiber and have low-frequency components.

[0104] For example, end-face reflections can cause saturation in the receiving circuit and ADC, and may also be too close to the target reflection signal in the spectrum, making signal identification difficult. Therefore, using a high-pass filter can attenuate these low-frequency end-face reflections, ensuring that the high-frequency components in the target reflection signal are not affected, thereby extracting target information more effectively and avoiding signal saturation problems.

[0105] Optionally, a notch filter, also known as a band-stop filter, is used to filter out specific frequencies or frequency ranges in a signal. When the frequency points of the end-face reflected signal and the target reflected signal are very close, a simple high-pass filter may not be able to effectively distinguish between them because their frequencies may be close to the passband range of the high-pass filter. In this case, a notch filter can more accurately filter out the end-face reflected frequency while keeping the target reflected frequency unaffected. This is merely an example; the type of filter used can be determined according to the actual situation. This is only an example distance and does not limit the type of filter used.

[0106] The following describes in detail another optional implementation method.

[0107] Currently, the frequency modulation characteristics of laser signals are used to accurately measure the distance and velocity of targets. Its working principle is based on the frequency difference between the emitted continuous-wave frequency-modulated laser signal and the laser signal reflected from the target, i.e., the Doppler frequency shift, to calculate the target's motion parameters. In frequency-modulated continuous-wave lidar, the OPA transceiver system is used for transmitting and receiving laser signals. However, the reflected signals from each coupling end face in the OPA system (end-face reflection signals) are unavoidable. Because the delay time of these signals is similar to that of the target reflected signal, the frequency points generated in the receiving circuit may overlap with or be very close to the target signal frequency points, potentially causing saturation of the amplifiers and ADCs (analog-to-digital converters) in the receiving circuit. Circuit saturation severely affects the accuracy and reliability of signal acquisition, leading to the inability to correctly extract target information. Moreover, during the signal processing stage, when the end-face reflection signal and the target signal frequency points are too close, the system has difficulty effectively distinguishing between the two. Especially when the target signal frequency point is very close to the end-face reflection frequency point, it may cause the target signal to be missed, meaning the system cannot correctly identify the target, or create a close-range measurement blind zone, meaning that target information cannot be accurately measured within a certain distance range.

[0108] Figure 5 This is an output waveform diagram of an ADC according to an embodiment of the present invention, such as... Figure 5 As shown, this visually illustrates the changes in the characteristics of the ADC output signal when the OPA transceiver receives a strong end-face reflection signal, and the potential system performance problems that may result from this.

[0109] The highest peak in the waveform represents the maximum output value of the ADC conversion. That is, when the input signal reaches the maximum amplitude it can process, the ADC will output the maximum code value. In a lidar system, if the intensity of the input signal (end-face reflection signal) is too large and exceeds the linear range of the ADC, it will cause the ADC output to saturate and fail to accurately reflect the true value of the input signal.

[0110] The low point in the middle of the waveform represents the ADC code value of 0. In signal processing, the code value of 0 usually corresponds to the reference point of ADC conversion, that is, the output value when the input signal is 0 or close to 0.

[0111] The lowest point of the waveform graph shows the minimum output value of the ADC conversion, which is usually related to the low noise level of the signal or the output when there is no signal input.

[0112] Optionally, by Figure 5 It is known that when the end-face reflection signal causes the ADC to saturate, the actual target reflection signal may not be accurately identified because the ADC output has reached its limit and cannot reflect subsequent signal changes. This can lead to the underidentification of the target signal, especially when the frequency of the target reflection signal is close to the frequency of the end-face reflection signal. In such cases, the system may be unable to distinguish between the two, resulting in a blind zone in close-range measurement.

[0113] In related technologies, to reduce the impact of end-face reflection signals on target reflection signals, high-pass or band-stop filters are typically added to the receiving circuit to attenuate the end-face reflection signal. However, when the frequency points of the target signal and the end-face reflection signal are very close, designing a suitable filter becomes extremely difficult. This includes flat-band design of the filter to achieve the desired frequency attenuation and avoiding unnecessary attenuation of the target signal. Furthermore, while designing a high-order filter can provide better frequency selectivity, it also leads to increased insertion loss, thereby affecting the overall ranging and velocity measurement performance of the system.

[0114] In related technologies, a gain feedback adjustment command is generated by determining whether the maximum amplitude of the sampled data from the ADC channel is within a threshold range. The programmable gain module then adjusts the gain coefficient of the ADC channel to eliminate the ADC sampling saturation problem caused by excessively strong reflection signals from the end face of the continuous laser velocimetry system. However, this method increases system complexity. Furthermore, reducing the gain coefficient of the programmable gain module when the ADC channel sampled data reaches the threshold leads to a decrease in signal gain, thereby reducing the system's ranging capability.

[0115] However, this invention provides a target object detection method based on lidar. By adjusting the optical path difference between the end-face reflection signal and the target signal, the position of the end-face reflection frequency point is changed, ensuring sufficient distance between it and the target signal frequency point to avoid frequency overlap. Then, based on the adjusted end-face reflection signal and target reflection signal, the passband and stopband frequencies of the filter are set to ensure that the filter effectively filters out the end-face reflection signal while keeping the target signal unaffected. The target object's position information is then detected based on the target reflection signal after the end-face reflection signal has been filtered out. This significantly improves the accuracy of target object position detection. Furthermore, by adjusting the optical path difference to increase the spectral distance between the end-face reflection frequency point and the target reflection frequency point, and setting the filter bandwidth based on the adjusted spectral distance, the difficulty of filter setup is greatly reduced, lowering system complexity and cost, while simultaneously improving signal processing accuracy and lidar ranging capability.

[0116] The method will be further described below.

[0117] Figure 6 This is a schematic diagram of a lidar system according to an embodiment of the present invention. Figure 6 The diagram illustrates the basic components and signal path of a lidar system, particularly the parts related to adjusting the reflection frequency at the end face and filter design. The laser generates a frequency-modulated continuous laser signal through modulation and splits it into two paths: one as the signal light and the other as the local oscillator light. The signal light is transmitted to the OPA transceiver via fiber 1, optical components, and fiber 2, while the local oscillator light serves as a reference signal, transmitted to the receiver via fiber 5. At the receiver, it interferes with the returned signal light to extract target reflection information. After receiving the signal light, the OPA transceiver transmits it to the target. The target reflects the signal light, and the reflected light is transmitted to the receiving circuit via the OPA transceiver, fiber 3, optical components, and fiber 4.

[0118] Optionally, when end-face reflection exists in the coupling portion of the OPA transceiver, part of the laser signal passing through fiber 2 directly reaches the receiving circuit via fiber 3, and is not transmitted through the OPA transceiver. After the ADC acquires the signal and performs Fourier transform, a fixed frequency point is generated. Furthermore, the intensity of end-face reflection is generally very strong, which can cause signal saturation in the amplifier and ADC, such as... Figure 5 When the frequency of the end face reflection is very close to the frequency of the target signal, such as... Figure 3 The frequency points reflected from the end face may be detected by the system, resulting in missed identification. Therefore, missed identification may occur near the frequency points reflected from the end face, forming a blind zone at close range.

[0119] Alternatively, to solve the above problems, a high-pass or notch filter is usually added before the amplifier and ADC. However, when the passband cutoff frequency and the stopband cutoff frequency are very close, the added filter not only cannot completely filter out the end-face reflection frequency, but will also attenuate the signal frequency. Figure 7 This is a schematic diagram illustrating the difference in frequency response characteristics between an ideal filter and a practical filter according to an embodiment of the present invention, as shown below. Figure 7 As shown, Figure 7 Figure (a) shows the end-face reflection frequency and signal frequency in the original state. Figure 7 Figure (b) shows the frequency response of the notch filter under ideal conditions. Figure 7 Figure (c) in the diagram shows the frequency response of the actual notch filter.

[0120] Optionally, by Figure 7 As shown in Figure (b), in an ideal notch filter, the passband gain is flat, allowing signal frequencies to pass through without loss. Simultaneously, the notch filter exhibits infinite attenuation at the end-face reflection frequency, meaning the signal at that point will be completely filtered out without affecting system performance. Theoretically, this characteristic can solve the interference problem of end-face reflection signals, protecting amplifiers and ADCs from saturation, while maintaining the integrity and identifiability of the target reflected signal.

[0121] Optionally, by Figure 7 As shown in Figure (c), practical filters cannot achieve ideal performance; that is, they cannot achieve perfect passband flatness and infinite stopband attenuation. In practical notch filters, there may be some gain non-flatness in the passband, which may cause slight attenuation of the signal frequency and affect signal quality. At the same time, the stopband attenuation is limited and cannot completely filter out end-face reflection frequencies, especially when the passband and stopband frequencies are very close.

[0122] Alternatively, in order to make the actual filter closer to the ideal filter, the only way is to increase the number of filter stages. However, the higher the stage, the more complex the filter becomes, the greater the insertion loss, and it is also impossible to simultaneously meet the requirements of a flat passband and a fast stopband attenuation.

[0123] Optionally, to reduce the difficulty of filter design and achieve optimal filter design, it is necessary to move the end-face reflection frequency and the signal frequency further apart, increasing the ratio of the end-face reflection frequency to the signal frequency. As shown in the aforementioned formula (1), the end-face reflection frequency is determined by the optical path difference between the reflection position and the local oscillator position, the modulation bandwidth, and the modulation period. Based on this, by increasing or decreasing the fiber length between the end-face reflection position and the local oscillator position, thereby changing the optical path difference, the end-face reflection frequency can be moved to a specified position. Figure 4 The effect was demonstrated.

[0124] Optionally, for the case of multiple end-face reflection frequencies, there are cases where the signal frequency is before the multiple end-face reflection frequencies, and cases where the signal frequency is only on the right side of the multiple end-face reflections. In this case, the optical path difference of each end-face reflection position can be changed. Figure 8 This is a comparative schematic diagram showing the optical path difference before and after changing the reflection frequency points of multiple end faces according to an embodiment of the present invention. Figure 8 As shown, the frequency of the reflected signal at each end face is adjusted by changing the fiber length of the reflection path at different end faces. The purpose of this adjustment is to ensure sufficient spectral distance between each end face reflection frequency and the target reflection frequency, thereby avoiding signal interference. By moving the end face reflection frequencies to locations farther from the signal frequencies, it becomes easier to design filters to suppress these reflected signals without adversely affecting the target signal.

[0125] Alternatively, by increasing the ratio of the end-face reflection frequency to the signal frequency, even low-order, simple filters can easily achieve optimal performance. Once the end-face reflection frequency and the signal frequency are determined, the filter's cutoff frequency and passband frequency can be determined. At this point, the design requirements can be met by adjusting the filter's order and zeros / pole points. Figure 9 This is a comparison diagram of the frequency response of a practically designed filter and an ideal filter according to an embodiment of the present invention, such as... Figure 9 As shown, changing the optical path difference alters the end-face reflection frequency, which, in conjunction with the filter design, achieves the optimal filter design.

[0126] In this embodiment of the invention, by designing a filter, the end face reflection signal in the target reflection signal can be effectively filtered out, thereby ensuring the integrity of the target reflection signal and improving the detection accuracy of the target object's position information.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0128] This embodiment also provides a lidar-based object detection device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0129] Figure 10 This is a structural block diagram of an object detection device based on lidar according to an embodiment of the present invention, such as... Figure 10 As shown, the device includes: a first detection unit 1001, a first determination unit 1002, an adjustment unit 1003, a second determination unit 1004, a filtering unit 1005, and a second detection unit 1006.

[0130] The first detection unit 1001 is used to detect the end face reflection signal and the target reflection signal in response to the signal light emitted by the laser being transmitted to the target object through optical devices and an optical phased array transceiver. The end face reflection signal is formed by reflection from the optical phased array transceiver and optical devices, and the target reflection signal is formed by reflection from the target object.

[0131] The first determining unit 1002 is used to determine the spectral distance between the end face reflection frequency point and the target reflection frequency point in the spectrum based on the end face reflection signal and the target reflection signal.

[0132] The adjustment unit 1003 is used to adjust the spectral distance in response to the spectral distance being less than the distance threshold.

[0133] The second determining unit 1004 is used to determine the passband frequency and stopband frequency of the filter based on the adjusted spectral distance, wherein the passband frequency is used to represent the frequency range of signals that the filter allows to pass through, and the stopband frequency is used to represent the frequency range of signals that the filter prohibits to pass through.

[0134] The filtering unit 1005 is used to control the filter to filter out the end face reflection signal in the target reflection signal according to the passband frequency and stopband frequency.

[0135] The second detection unit 1006 is used to detect the position of the target object based on the filtered target reflection signal.

[0136] The object detection device based on lidar provided in this embodiment of the invention uses a first detection unit 1001 to detect end-face reflection signals and target reflection signals in response to the signal light emitted by the laser being transmitted to the target object through optical devices and an optical phased array transceiver. The end-face reflection signal is formed by reflection from the optical phased array transceiver and optical devices, and the target reflection signal is formed by reflection from the target object.

[0137] The first determining unit 1002 is used to determine the spectral distance between the end-face reflection frequency point and the target reflection frequency point in the spectrum based on the end-face reflection signal and the target reflection signal; the adjusting unit 1003 is used to adjust the spectral distance in response to the spectral distance being less than a distance threshold; the second determining unit 1004 is used to determine the passband frequency and stopband frequency of the filter based on the adjusted spectral distance, wherein the passband frequency is used to represent the frequency range of signals that the filter allows to pass through, and the stopband frequency is used to represent the frequency range of signals that the filter prohibits to pass through; the filtering unit 1005 is used to control the filter to filter out the end-face reflection signal in the target reflection signal according to the passband frequency and the stopband frequency; the second detection unit 1006 is used to detect the position of the target object based on the filtered target reflection signal, thereby effectively extracting the target reflection signal from the received signal, and then accurately calculating the position of the target object based on the extracted target reflection signal, thereby improving the detection accuracy of the target object's position information and solving the technical problem in related technologies where the target reflection signal and the end-face reflection signal are difficult to distinguish, resulting in inaccurate detection of the target object's position information.

[0138] It should be noted that the above-mentioned units can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above-mentioned units are located in the same processor; or, the above-mentioned units are located in different processors in any combination.

[0139] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0140] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0141] Figure 11 This is a schematic diagram of the structure of an electronic device for a lidar-based object detection method according to an embodiment of the present invention, as shown below. Figure 11 As shown, an embodiment of the present invention also provides an electronic device 1100, including a processor 1101 and a memory 1102, wherein the memory 1102 stores a computer program, and the processor 1101 is configured to run the computer program to perform the steps in any of the above method embodiments.

[0142] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0143] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0144] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0145] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for object detection based on lidar, characterized in that, include: In response to the signal light emitted by the laser, it is transmitted to the target object through optical devices and an optical phased array transceiver to detect the end face reflection signal and the target reflection signal. The end face reflection signal is formed by reflection by the optical phased array transceiver and the optical devices, and the target reflection signal is formed by reflection by the target object. Based on the end face reflection signal and the target reflection signal, determine the spectral distance between the end face reflection frequency point and the target reflection frequency point in the spectrum; In response to the spectral distance being less than a distance threshold, the spectral distance is adjusted; Based on the adjusted spectral distance, the passband frequency and stopband frequency of the filter are determined, wherein the passband frequency is used to represent the frequency range of signals that the filter allows to pass, and the stopband frequency is used to represent the frequency range of signals that the filter prohibits from passing. The filter is controlled to filter out the end-face reflection signal from the target reflection signal according to the passband frequency and stopband frequency; The position of the target object is detected based on the filtered target reflection signal.

2. The object detection method according to claim 1, characterized in that, Based on the end-face reflection signal and the target reflection signal, the spectral distance between the end-face reflection frequency point and the target reflection frequency point in the spectrum is determined, including: The end-face reflection signal is mixed with the local oscillator signal of the laser to generate a first difference frequency signal corresponding to the end-face reflection signal, and the target reflection signal is mixed with the local oscillator signal to generate a second difference frequency signal corresponding to the target reflection signal, wherein the local oscillator signal is a reference signal emitted by the laser with the same frequency as the signal light; The spectral distance is determined based on the first difference frequency signal and the second difference frequency signal.

3. The object detection method according to claim 2, characterized in that, Determining the spectral distance based on the first difference frequency signal and the second difference frequency signal includes: The first difference frequency signal is converted into a first digital signal and the second difference frequency signal is converted into a second digital signal using an analog-to-digital converter. The end face reflection frequency point is obtained by performing a Fourier transform on the first digital signal, and the target reflection frequency point is obtained by performing a Fourier transform on the second digital signal. The spectral distance is determined based on the position of the end-face reflection frequency point in the spectrum and the position of the target reflected signal in the spectrum.

4. The object detection method according to claim 1, characterized in that, The end-face reflection frequency is associated with the optical path difference between the end-face reflection position of the optical phased array transceiver and the local oscillator position of the laser, and the optical path difference is associated with the fiber length between the end-face reflection position and the local oscillator position. Adjusting the spectral distance includes: Determine the target fiber length between the end face reflection position of the optical phased array transceiver and the local oscillator position of the laser, wherein the target fiber length is used to represent the fiber length that makes the spectral distance between the end face reflection frequency point and the target reflection frequency point satisfy a distance threshold; The current fiber length between the end-face reflection position and the local oscillator position is adjusted to the target fiber length to adjust the spectral distance between the end-face reflection frequency point and the target reflection frequency point.

5. The object detection method according to claim 4, characterized in that, The spectral distance between the adjusted end-face reflection frequency and the target reflection frequency is greater than the distance threshold.

6. The object detection method according to claim 1, characterized in that, Based on the adjusted spectral distance, the passband frequency and stopband frequency of the filter are determined, including: Based on the adjusted spectral distance, the passband frequency and stopband frequency of the filter are determined, and the adjusted end-face reflection frequency and the adjusted target reflection frequency are determined. Based on the adjusted end-face reflection frequency and the adjusted target reflection frequency, the passband frequency and stopband frequency of the filter are determined.

7. The object detection method according to claim 6, characterized in that, The passband frequency of the filter covers the target reflection frequency, and the stopband frequency of the filter covers the end face reflection frequency.

8. The object detection method according to claim 7, characterized in that, The filter is at least a high-pass filter or a notch filter.

9. An object detection device based on lidar, characterized in that, include: The first detection unit is used to detect the end face reflection signal and the target reflection signal in response to the signal light emitted by the laser being transmitted to the target object through optical devices and an optical phased array transceiver. The end face reflection signal is formed by reflection from the optical phased array transceiver and the optical devices, and the target reflection signal is formed by reflection from the target object. The first determining unit is used to determine the spectral distance between the end face reflection frequency point and the target reflection frequency point in the spectrum based on the end face reflection signal and the target reflection signal; An adjustment unit is configured to adjust the spectral distance in response to the spectral distance being less than a distance threshold. The second determining unit is used to determine the passband frequency and stopband frequency of the filter based on the adjusted spectral distance, wherein the passband frequency is used to represent the frequency range of signals that the filter allows to pass through, and the stopband frequency is used to represent the frequency range of signals that the filter prohibits to pass through; A filtering unit is used to control the filter to filter out the end-face reflection signal in the target reflection signal according to the passband frequency and the stopband frequency; The second detection unit is used to detect the position of the target object based on the filtered target reflection signal.

10. A processor, characterized in that, The processor is used to run a program, wherein the program is executed by the processor to perform the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the method described in any one of claims 1 to 8 when it is run.

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