A signal processing system for a lidar

Abstract

This application provides a signal processing system for a lidar system, comprising: a detector, a sampling module, an amplification circuit, and a nonlinear correction loop. The detector converts the laser echo signal from an optical signal into an electrical signal. The amplification circuit amplifies the echo electrical signal according to a gain control signal sent by the nonlinear correction loop. The nonlinear correction loop sends the gain control signal to the amplification circuit, selects a sampling module from a set of sampling modules based on a first spectral characteristic, and samples the amplified echo electrical signal through the selected sampling module. This application solves the problem in related technologies where the gain of the amplification circuit is fixed or inflexible, affecting the accuracy of subsequent signal processing. It ensures the linearity of signal processing and the stability of signal strength, and to a certain extent avoids nonlinear distortion.

Description

Technical Field

[0001] This application relates to the field of lidar technology, and more specifically, to a lidar signal processing system. Background Technology

[0002] FMCW (Frequency Modulated Continuous Wave) lidar technology has been widely used in various fields such as autonomous vehicles, robot navigation, environmental monitoring, and topographic mapping due to its advantages in ranging accuracy, anti-interference capability, and cost-effectiveness.

[0003] However, FMCW lidar faces a series of pressing technical challenges in signal processing, especially in high-speed, high-precision scanning scenarios where these challenges become even more pronounced. In related technologies, the fixed or inflexible gain of the amplifier circuit in FMCW lidar easily introduces nonlinear distortion, causing irregular changes in the signal amplitude characteristics and affecting the accuracy of subsequent signal processing. Summary of the Invention

[0004] This application provides a signal processing system for lidar, which at least solves the technical problem in related technologies where the gain of the amplifier circuit is fixed or inflexible, easily introducing nonlinear distortion and affecting the accuracy of subsequent signal processing.

[0005] According to one aspect of the embodiments of this application, a signal processing system for a lidar is provided. The signal processing system includes a detector, an amplification module, and a sampling module. The amplification module includes an amplification circuit and a nonlinear correction loop. The sampling module includes a set of sampling modules. The detector is connected to the amplification circuit, and the amplification module is connected to the sampling module.

[0006] The detector is used to receive the laser echo signal reflected by the target, convert the laser echo signal from an optical signal into an echo electrical signal, and send the converted echo electrical signal to the amplifier circuit.

[0007] An amplifier circuit is used to amplify the echo signal according to the gain control signal sent by the nonlinear correction loop, and then send the amplified echo signal to the nonlinear correction loop.

[0008] The nonlinear correction loop is used to perform signal detection processing on the amplified echo signal to obtain the signal detection result. Based on the signal detection result, the gain control signal is adjusted and sent to the amplification circuit; the first spectral characteristic of the amplified echo signal is detected.

[0009] A sampling module is used to receive a first spectral characteristic provided by a nonlinear correction loop, select a sampling module from a set of sampling modules based on the first spectral characteristic, and sample the amplified echo signal through the selected sampling module; wherein, the multiple sampling modules in the sampling module correspond to different spectral ranges. Through this application, an amplification circuit is used to amplify the echo signal according to a gain control signal sent by the nonlinear correction loop, and send the amplified echo signal to the nonlinear correction loop; the nonlinear correction loop is used to perform signal detection processing on the amplified echo signal, obtain a signal detection result, adjust the gain control signal according to the signal detection result, and send it to the amplification circuit; detect the first spectral characteristic of the amplified echo signal; the sampling module is used to receive the first spectral characteristic provided by the nonlinear correction loop, select a sampling module from a set of sampling modules based on the first spectral characteristic, and sample the amplified echo signal through the selected sampling module; wherein, the multiple sampling modules in the sampling module correspond to different spectral ranges. In the embodiments of this application, a nonlinear correction loop is used to solve the problem in related technologies where the gain of the amplifier circuit is fixed or inflexible, affecting the accuracy of subsequent signal processing. This ensures the linearity of signal processing and the stability of signal strength, and avoids nonlinear distortion to a certain extent. Furthermore, by dynamically adjusting the amplifier circuit gain and intelligently selecting the sampling module, a flexible response to changes in signal strength and frequency fluctuations is achieved, significantly reducing signal distortion and sampling errors, improving the overall accuracy and stability of signal processing, and thus improving the accuracy of parameter information (such as distance, speed, position, etc.) extracted from the signal. Attached Figure Description

[0010] Figure 1 This is a structural block diagram of an optional lidar signal processing system according to an embodiment of this application;

[0011] Figure 2 This is a structural block diagram of an optional amplification module according to an embodiment of this application;

[0012] Figure 3 This is a structural block diagram of an optional testing system in an embodiment of this application;

[0013] Figure 4 This is a structural block diagram of another optional test system in the embodiments of this application;

[0014] Figure 5 This is a structural block diagram of another optional lidar signal processing system according to an embodiment of this application;

[0015] Figure 6 This is a structural block diagram of another optional testing system according to an embodiment of this application;

[0016] Figure 7 This is a structural block diagram of an optional second sampling module according to an embodiment of this application;

[0017] Figure 8 This is a structural block diagram of another optional lidar signal processing system in the embodiments of this application;

[0018] Figure 9 This is a schematic diagram illustrating an optional comparison between a standard signal and a sampled signal in an embodiment of this application. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] According to one aspect of the embodiments of this application, an optional signal processing system for lidar is provided. Figure 1 This is a structural block diagram of an optional lidar signal processing system according to an embodiment of this application, such as... Figure 1 As shown, the signal processing system includes a detector, an amplification module, and a sampling module. The amplification module includes an amplification circuit and a nonlinear correction loop. The sampling module includes a set of sampling modules. The detector is connected to the amplification circuit, and the amplification module is connected to the sampling module.

[0022] The detector is used to receive the laser echo signal reflected by the target, convert the laser echo signal from an optical signal into an echo electrical signal, and send the converted echo electrical signal to the amplifier circuit.

[0023] An amplifier circuit is used to amplify the echo signal according to the gain control signal sent by the nonlinear correction loop, and then send the amplified echo signal to the nonlinear correction loop.

[0024] The nonlinear correction loop is used to perform signal detection processing on the amplified echo signal to obtain the signal detection result. Based on the signal detection result, the gain control signal is adjusted and sent to the amplification circuit; the first spectral characteristic of the amplified echo signal is detected.

[0025] The sampling module is used to receive the first spectral characteristics provided by the nonlinear correction loop, select a sampling module from a set of sampling modules according to the first spectral characteristics, and sample the amplified echo signal through the selected sampling module; wherein, the multiple sampling modules in the sampling module correspond to different spectral ranges.

[0026] The LiDAR signal processing system in this embodiment can be applied to the field of LiDAR technology, including scenarios such as autonomous driving, robot navigation, terrain mapping, and security monitoring. In related technologies, LiDAR devices used in autonomous driving, robot navigation, terrain mapping, and security monitoring scenarios include LiDAR signal processing systems. These systems typically include a detector, an amplifier circuit, and a sampling module. The detector converts the received optical echo signal into an electrical signal, the amplifier circuit amplifies the electrical signal, and the sampling module samples the amplified signal for signal processing and information extraction. However, when processing echo signals with large fluctuations in signal strength and a wide frequency range, especially in scenarios with significant signal strength variations, the fixed or inflexible gain of the amplifier circuit in these traditional systems can easily introduce nonlinear distortion, leading to irregular changes in the signal amplitude characteristics and affecting the accuracy of subsequent signal processing.

[0027] To at least partially solve the aforementioned technical problems, this embodiment includes a nonlinear correction loop in the amplification module. This loop, through signal detection and processing, sends a gain control signal to the amplification circuit when the signal detection result indicates that the gain needs adjustment. This dynamically adjusts the gain to ensure the linearity of signal processing and the stability of signal strength, avoiding nonlinear distortion. Furthermore, by dynamically adjusting the amplification circuit gain and intelligently selecting the sampling module, a flexible response to changes in signal strength and frequency fluctuations is achieved, significantly reducing signal distortion and sampling errors, improving the overall accuracy and stability of signal processing, and thus enhancing the accuracy of parameter information extracted from the signal (such as distance, velocity, and position). It should be noted that in the signal processing system of a lidar, the detector mainly consists of photoelectric conversion components such as photodiodes or avalanche photodiodes (APDs), used to receive the laser echo signal reflected from the target and convert the optical signal into an electrical signal for subsequent circuit processing. The amplification module includes an amplification circuit, which is a key component of the lidar signal processing system, primarily responsible for amplifying the received weak electrical signal. The amplification module typically includes one or more cascaded amplifiers, enabling multi-stage amplification of the signal. These amplifiers are usually designed with high gain, low noise, and wide bandwidth to handle electrical signals of various intensities and frequencies. The sampling module may include a set of sampling modules, each processing the signal according to its spectral characteristics. The target can refer to the object that the lidar system attempts to detect and measure; it can be a static object, such as a building, tree, or road sign, or a dynamic object, such as a vehicle, pedestrian, or animal. The laser echo signal reflected from the target is the basis for the lidar system to perform ranging and positioning.

[0028] When a lidar system emits laser pulses, these pulses interact with the target, and some of the light is reflected back to the lidar. The detector is responsible for capturing these reflected light signals, known as laser echo signals. In other words, laser echo signals refer to the laser signals reflected from the target and returning to the lidar system. These echo signals carry information about the target's distance and velocity. When the detector converts the laser echo signals into electrical signals, the resulting electrical signals are called echo signals. Similarly, the echo signals carry information about the target's distance and velocity.

[0029] Specifically, to better understand this in a real-world scenario, let's take a car as an example. A lidar system emits laser pulses towards a car, which reflects some of the laser light. The detector captures this reflected laser light, known as the laser echo signal. The detector contains photodiodes or other photoelectric conversion elements that convert the received optical signal into a corresponding electrical signal. This electrical signal is the echo signal, which is then sent to an amplifier circuit for further processing.

[0030] The amplification module may include an amplification circuit and a nonlinear correction loop. The amplification circuit in the amplification module is directly connected to the detector. After the detector converts the laser echo signal from an optical signal to an electrical signal, the converted echo signal is transmitted to the amplification circuit in the amplification module. The amplification circuit performs preliminary amplification on the received echo signal and sends the amplified echo signal to the nonlinear correction loop in the amplification module. The nonlinear correction loop performs signal detection processing on the received amplified echo signal to obtain a signal detection result. Optionally, if the signal detection result indicates that the gain of the amplification circuit needs to be adjusted, the nonlinear correction loop will send a gain control signal to adjust the gain of the amplification circuit. The amplification circuit then re-amplifies the echo signal based on the adjusted gain. It should be noted that the signal detection processing is an analysis process performed on the amplified signal to evaluate the signal strength, frequency characteristics, and possible nonlinear distortion. The result of the signal detection processing is used to generate a gain control signal to guide the gain adjustment of the amplification circuit, which can either decrease or increase the gain of the amplification circuit.

[0031] Each signal that passes through the amplifier circuit needs to be detected and processed by the nonlinear correction loop to obtain the signal detection result. If the signal detection result indicates that the gain of the amplifier circuit does not need to be adjusted, then the signal is determined to be unadjustable. That is, the echo signal after amplification is a signal that does not need to be re-amplified, so as to ensure that the signal is amplified under the best conditions, reduce nonlinear distortion, and thus prepare for subsequent sampling.

[0032] Specifically, when a lidar system emits a laser pulse towards a car, and the detector sends an echo signal to the amplification circuit, the amplification circuit amplifies the signal to an appropriate level and then sends the amplified echo signal to the nonlinear correction loop. When the intensity of the laser reflected from the car suddenly increases, the nonlinear correction loop detects the nonlinear change in the signal and sends a gain control signal to the amplification circuit, instructing it to reduce the gain. The amplification circuit adjusts the gain according to the gain control signal, re-amplifies the signal, and sends it back to the nonlinear correction loop for detection and analysis. It should be noted that the nonlinear correction loop performs signal detection processing on every amplified signal transmitted by the amplification circuit.

[0033] After determining that the gain of the amplifier circuit does not need to be adjusted based on the amplified echo signal, the first spectral characteristic of the amplified echo signal can be detected. From a set of sampling modules, a suitable sampling module is selected for the echo signal. The first spectral characteristic refers to the frequency composition and distribution of the amplified echo signal. Multiple sampling modules in the sampling module correspond to different spectral ranges. By using the first spectral characteristic, the most suitable sampling module for the signal frequency band can be intelligently selected to achieve the best signal sampling effect. The number of sampling modules selected for the echo signal can be one or more.

[0034] It should be noted that when the nonlinear correction loop in the amplification module sends the amplified echo signal to the sampling module, the selected sampling module samples the amplified echo signal to obtain the sampled echo signal. This sampled echo signal is in digital form and can be used to extract parameter information of specified parameters of the detected target. The specified parameters of the detected target may include at least one of the following: range, velocity, position, and reflection intensity. This information is crucial for the positioning and ranging functions of the lidar system and is one of the main outputs of the lidar system.

[0035] Each sampling module in a set of sampling modules can be connected to a signal processing unit. For example, when a lidar system emits a laser pulse towards a car to obtain relevant parameter information about the vehicle, the signal processing unit can accurately calculate the distance between the car and the lidar by analyzing the time and phase information of the sampled echo electrical signal. By analyzing the changes in signal strength and time information, the vehicle's speed relative to the lidar can be estimated. This parameter information is crucial for the lidar system to identify and track targets.

[0036] According to the embodiments provided in this application, an amplification circuit is used to amplify the echo signal according to the gain control signal sent by the nonlinear correction loop, and send the amplified echo signal to the nonlinear correction loop; the nonlinear correction loop is used to perform signal detection processing on the amplified echo signal, obtain a signal detection result, adjust the gain control signal according to the signal detection result, and send it to the amplification circuit; detect the first spectral characteristics of the amplified echo signal; a sampling module is used to receive the first spectral characteristics provided by the nonlinear correction loop, select a sampling module from a group of sampling modules according to the first spectral characteristics, and sample the amplified echo signal through the selected sampling module; wherein, multiple sampling modules in the sampling module correspond to different spectral ranges. In the embodiments of this application, the nonlinear correction loop solves the problem in related technologies where the gain of the amplification circuit is fixed or inflexible, affecting the accuracy of subsequent signal processing, ensuring the linearity of signal processing and the stability of signal strength, and avoiding nonlinear distortion to a certain extent. Furthermore, by dynamically adjusting the amplifier circuit gain and intelligently selecting the sampling module, a flexible response to changes in signal strength and frequency fluctuations is achieved, significantly reducing signal distortion and sampling errors, improving the overall accuracy and stability of signal processing, and thus improving the accuracy of parameter information (such as distance, speed, position, etc.) extracted from the signal.

[0037] In one exemplary embodiment, Figure 2 This is a structural block diagram of an optional amplification module according to an embodiment of this application. For example... Figure 2 As shown, the nonlinear correction loop includes a detector circuit and a gain control circuit. The amplifier circuit is connected to both the detector circuit and the gain control circuit. The detector circuit is connected to both the gain control circuit and the sampling module.

[0038] The detection circuit is used to detect and process the amplified echo signal to obtain the signal detection result, and then send the signal detection result to the gain control circuit.

[0039] The gain control circuit is used to generate a gain control signal based on the signal detection result and send the gain control signal to the amplifier circuit. The gain control signal is used to indicate the amplification factor of the amplifier circuit.

[0040] Specifically, the nonlinear correction loop, as a core component, significantly improves the performance and reliability of the lidar signal processing system. The nonlinear correction loop consists of a detection circuit and a gain control circuit; these two parts work together to achieve dynamic gain adjustment and nonlinear correction during signal processing.

[0041] The main function of the detector circuit is to perform signal detection processing on the amplified echo signal in order to evaluate the signal strength and spectral characteristics. The signal detection results can be used to determine whether the gain of the amplifier circuit needs to be adjusted.

[0042] Optionally, the signal detection processing of the detection circuit may include at least one of the following methods: envelope detection processing, spectrum analysis processing, and level detection processing. Specifically, the detection circuit uses envelope detection technology to extract the envelope information of the amplified echo signal, i.e., the curve showing the amplitude of the amplified echo signal changing over time. When the curve showing the amplitude of the amplified echo signal changing over time determines that the gain of the amplifier circuit needs adjustment, the signal detection result is fed back to the gain control circuit. The gain control circuit generates a gain control signal based on the signal detection result and sends the gain control signal to the amplifier circuit to adjust the gain of the amplifier circuit.

[0043] In addition to envelope detection, the detection circuit can also perform spectrum analysis to evaluate the frequency components and distribution of the amplified echo signal. By processing the signal detection results through spectrum analysis and determining that the gain of the amplifier circuit needs adjustment, the signal detection results are fed back to the gain control circuit. The gain control circuit generates a gain control signal based on the signal detection results and sends this signal to the amplifier circuit to adjust its gain.

[0044] Level detection processing is a method for monitoring signal levels. The detection circuit can preprocess the amplified echo signal to obtain a signal processing result containing the level value. When it is determined that the gain of the amplifier circuit needs to be adjusted, the signal detection result is fed back to the gain control circuit. The gain control circuit generates a gain control signal based on the signal detection result and sends the gain control signal to the amplifier circuit to adjust the gain of the amplifier circuit.

[0045] When the detection circuit sends the signal detection result to the gain control circuit, the gain control circuit generates a corresponding gain control signal based on the received signal detection result to adjust the gain of the amplifier circuit. The gain control information can be used to indicate the amplification factor of the amplifier circuit.

[0046] In practice, the amplifier circuit initially amplifies the echo signal, and then the detector circuit performs signal detection processing on the received amplified echo signal. If the signal detection result indicates that the gain of the amplifier circuit needs adjustment, the detector circuit sends the signal detection result to the gain control circuit. Based on the signal detection result, a gain control signal is generated and fed back to the amplifier circuit to dynamically adjust its gain. The adjusted signal is then retransmitted to the detector circuit in the nonlinear correction loop for further analysis and processing to ensure that the signal quality meets the requirements of the subsequent sampling module.

[0047] Optionally, the gain control circuit can gradually adjust the gain of the amplifier circuit according to a preset step size, or it can analyze the signal detection results through a preset algorithm to obtain the required amplification factor of the amplifier circuit, so as to adjust the gain of the amplifier circuit.

[0048] In practice, before constructing the signal processing system of a lidar system, each component can be analyzed and tested individually. For example, in one instance, the amplification module can be tested, and based on the test results, the individual components within the amplification module can be adjusted. Specifically... Figure 3 As shown, Figure 3 This is a structural block diagram of an optional test system in an embodiment of this application. The test system may include an arbitrary waveform generator, an amplifier circuit, a detector circuit, a gain control circuit, and a sampling analysis and correction unit.

[0049] In the testing system, the sampling analysis corrector first controls the arbitrary waveform generator to generate an original signal with a known frequency and amplitude. The arbitrary waveform generator, based on the control of the sampling analysis corrector, generates an original signal carrying specific harmonics. The original signal is input to the amplification module to obtain an amplified signal. The sampling analysis corrector receives the amplified signal output by the amplification module and compares it with the original signal.

[0050] pass Figure 3 The test system shown can further improve the linearity of the amplifier circuit and mitigate the effects of gain nonlinearity by adjusting the gain control circuit through frequency feedback of the harmonics of the detected signal.

[0051] In another example, the amplification and sampling modules can also be tested, and the individual components within these modules can be adjusted based on the test results. Specifically, as follows... Figure 4 As shown, Figure 4 This is a block diagram of another optional test system in the embodiments of this application, wherein the test system may include an arbitrary waveform generator, an amplifier circuit, a detector circuit, a gain control circuit, a sampling module, and a sampling analysis and correction unit.

[0052] In the testing system, the sampling analysis and corrector first controls an arbitrary waveform generator to produce raw signals with known frequencies and amplitudes. These raw signals then enter the amplification module, undergo amplification, and finally reach the sampling module. The sampling module is responsible for converting analog signals into digital signals for subsequent digital signal processing and analysis. The sampling analysis and corrector receives the digital signal output from the sampling circuit and compares it with the raw signal input to the system front end. Through this comparison process, the nonlinear information of the circuit system, including the amplification and sampling modules, can be accurately obtained, thereby achieving precise evaluation and correction.

[0053] Through this embodiment, by using the synergy of the detection circuit and the gain control circuit, the lidar system can achieve comprehensive monitoring of signal strength and spectral characteristics, dynamically adjust the gain to optimize the linearity and signal-to-noise ratio of signal processing, thereby effectively reducing signal distortion and improving the accuracy and reliability of signal processing.

[0054] In an exemplary embodiment, a detection circuit is used to perform envelope detection on the amplified echo signal to obtain signal envelope parameter values, wherein the signal envelope parameter values ​​include at least one of the following: envelope variance, envelope peak-to-peak value, envelope mean value, and the signal detection result includes the signal envelope parameter values; if the signal envelope parameter values ​​are not within a first value range, the signal envelope parameter values ​​are sent to a gain control circuit;

[0055] Gain control circuit is used to generate gain control signal based on signal envelope parameter values.

[0056] It should be noted that the detection circuit can be responsible for performing envelope detection on the amplified echo signal to obtain the signal envelope parameter values. Envelope detection is a signal processing technique used to extract the envelope curve of the signal amplitude as a function of time.

[0057] Signal envelope parameters refer to the signal characteristic values ​​obtained through envelope detection, specifically including but not limited to envelope variance, peak-to-peak value, and mean value. These parameters directly reflect the signal's intensity variations and stability, and are important indicators for evaluating signal quality. Envelope variance describes the magnitude of signal envelope fluctuations; a smaller variance indicates better signal stability. Peak-to-peak value represents the difference between the maximum and minimum values ​​of the signal envelope, used to measure the signal's dynamic range. The mean value reflects the average level of the signal envelope, helping to determine the signal's average strength.

[0058] Optionally, a preset value range can be set. This first value range is a pre-defined reasonable range for the signal envelope parameter values, closely related to the system's optimal operating state. When the signal envelope parameter values ​​are within this first range, it indicates that the system is operating in an ideal state, with minimal signal distortion and noise. Optionally, the first value range is a range obtained during testing of the lidar's signal processing system.

[0059] In one example, for a lidar system operating in a certain mode, the ideal signal envelope mean value should be between 1V and 2V. If the detection circuit detects that the signal envelope mean value is below 1V, it instructs the amplifier circuit to increase the gain; if the signal envelope mean value exceeds 2V, it instructs the amplifier circuit to decrease the gain. This dynamic adjustment mechanism ensures that the signal is always within the optimal operating range, avoiding distortion caused by signal saturation or excessive weakness.

[0060] In another example, if the signal envelope variance exceeds a preset first range (e.g., 0.1V to 0.3V), it indicates excessive signal strength fluctuation, which may lead to system instability. In this case, the gain control circuit dynamically generates a gain control signal based on the magnitude of the signal envelope variance, adjusting the gain of the amplifier circuit to reduce signal strength fluctuations and improve system stability.

[0061] In this embodiment, a detection circuit is used to perform envelope detection on the amplified echo signal to obtain the signal envelope parameter value. This enables real-time monitoring of the amplified echo signal, allowing for dynamic adjustment of the amplifier circuit gain via a gain control circuit. This reduces signal distortion and noise, improving the reliability of the lidar. Furthermore, by controlling the amplifier circuit gain, signal strength is prevented from exceeding the system's operating range, reducing system failures caused by signal saturation or weakness, and improving the overall stability of the lidar system.

[0062] In an exemplary embodiment, a detection circuit is used to perform spectral analysis on the amplified echo signal to obtain a second spectral characteristic, and send it to a gain control circuit, wherein the signal detection result includes the second spectral characteristic.

[0063] A gain control circuit is used to generate a gain control signal based on the second spectral characteristics.

[0064] It should be noted that the detection circuit can perform spectral analysis on the amplified echo signal to obtain its second spectral characteristics. These second spectral characteristics reflect the amplitude and phase changes of the amplified echo signal at different frequencies. By analyzing these second spectral characteristics, it is possible to identify whether the amplified echo signal exhibits nonlinear distortion, such as amplitude distortion or phase distortion. During signal processing, if the amplitude or phase changes of the signal are not proportional to the original signal, nonlinear distortion occurs. Specific types include amplitude distortion and phase distortion. Amplitude distortion refers to a nonlinear relationship between the signal amplitude change and the input signal; phase distortion refers to a nonlinear relationship between the signal phase change and the input signal.

[0065] Optionally, if the amplified echo signal exhibits nonlinear distortion as indicated by the second spectral characteristic, the second spectral characteristic is sent to the gain control circuit to generate a gain control signal based on the second spectral characteristic. This signal is used to adjust the gain of the amplifier circuit to optimize the signal processing and prevent signal saturation or weakness. Specifically, a preset intensity range or a preset amplification variation can be set to determine whether the amplification factor of the amplifier circuit needs adjustment. Optionally, a gain control signal is generated when preset conditions are met. The preset conditions can be at least one of the following: the minimum signal strength indicated by the second spectral characteristic is less than the minimum value of the preset intensity range; the maximum signal strength indicated by the second spectral characteristic is greater than the maximum value of the preset intensity range; the amplitude attenuation indicated by the second spectral characteristic is greater than a preset attenuation level; and the amplitude enhancement indicated by the second spectral characteristic is greater than a preset enhancement level. The signal strength indicated by the second spectral characteristic can be signal strength information obtained after spectral analysis of the amplified echo signal by the detection circuit. The signal strength in the second spectral characteristic can be the amplitude value at a specific frequency point or the comprehensive intensity value over the entire frequency range. The preset intensity range can be a set of upper and lower limits of signal strength pre-set during system design based on operational requirements and performance objectives. The purpose of setting the preset intensity range is to ensure that the signal strength during signal processing is neither too strong, leading to saturation, nor too weak, affecting detection accuracy.

[0066] In spectral analysis, amplitude attenuation refers to the degree to which the amplitude of a specific frequency component in the spectrum of a signal decreases compared to the original signal amplitude after amplification. Amplitude attenuation reflects the linearity of the amplifier circuit when processing signals. Nonlinear distortion causes amplitude attenuation at certain frequencies, while an ideal amplifier circuit should maintain the signal amplitude constant or amplify it proportionally. The second spectral characteristic, amplitude enhancement, is the opposite of amplitude attenuation; amplitude enhancement refers to the degree to which the amplitude of a specific frequency component in the spectrum of a signal increases compared to the original signal amplitude after amplification. Amplitude enhancement is also a manifestation of nonlinear distortion, especially noticeable when the signal approaches the saturation point of the amplifier circuit.

[0067] The preset attenuation level can be the maximum amplitude attenuation allowed in the system design; attenuation exceeding this preset value is considered unacceptable nonlinear distortion. The setting of the preset attenuation level depends on the signal quality requirements of the lidar system, such as accuracy, resolution, and dynamic range. The preset enhancement level is the maximum amplitude enhancement allowed in the design; enhancement exceeding this preset value is also considered unacceptable distortion.

[0068] In one example, for instance, in a lidar system operating in a certain mode, the preset signal strength range is 0.5V to 1.5V, with preset attenuation and enhancement levels of ±10%. The detection circuit, through spectrum analysis, detects the following after signal processing: the signal strength at a certain frequency is attenuated by 15%, exceeding the preset 10% (preset attenuation range); or the minimum signal strength is 0.3V, below 0.5V (the minimum of the preset strength range). In response to these situations, the detection circuit sends a second spectral characteristic to the gain control circuit. The gain control circuit recognizes that both the minimum signal strength and the amplitude attenuation exceed the preset range, and therefore generates a gain control signal, instructing the amplifier circuit to adjust the gain to compensate for insufficient signal strength and excessive amplitude attenuation.

[0069] In this embodiment, by dynamically adjusting the gain of the amplifier circuit, the gain control circuit can effectively correct nonlinear distortion and maintain the linearity of the signal during the amplification process, thereby improving the ranging accuracy and data reliability of the lidar system.

[0070] In an exemplary embodiment, a detection circuit is used to rectify and low-pass filter the amplified echo signal to obtain a DC signal value of the amplified echo signal, and send the DC signal value to a gain control circuit. The signal detection result includes the DC signal value, which is used to represent the average intensity of the amplified echo signal.

[0071] Gain control circuit, used to generate gain control signal based on DC signal value.

[0072] It should be noted that a rectifier (such as a diode rectifier) ​​can be included in the detection circuit. The rectifier converts the AC signal into a full-wave or half-wave rectified signal. The function of the rectifier is to flip the negative half-cycle of the signal to the positive half-cycle, thereby eliminating the negative part of the signal and retaining only the absolute value. The low-pass filter further filters out high-frequency noise, ensuring that the output DC signal value accurately reflects the average signal strength. The DC signal value is calculated by averaging the rectified signal to obtain the average signal strength.

[0073] Optionally, a second value range can be set to determine whether the signal strength is within the ideal detection range. This range is typically based on the system's operating requirements and the expected signal dynamic range. If the DC signal value falls within the second value range, it indicates that the signal is within the system's effective processing range; if it exceeds the range, it means the signal strength is too strong or too weak, requiring adjustment of the amplifier circuit's gain.

[0074] The gain control circuit dynamically generates a gain control signal based on the DC signal value output by the detector circuit, in order to adjust the amplification factor, i.e., the gain, of the amplifier circuit. Specifically, the gain control signal is generated when the DC signal value is greater than the maximum value of the second value range or when the DC signal value is less than the minimum value of the second value range.

[0075] In one example, for instance, in a specific operating mode of a lidar system, the second value range is set to 0.5V to 1.5V. This means that the average signal strength should remain within this range to ensure optimal system performance. When the detection circuit detects a DC signal value of 1.8V, meaning the signal strength is greater than the maximum value of the second range (1.5V), it indicates that the signal may be saturated. In this case, the detection circuit sends the DC signal value to the gain control circuit, which generates a gain control signal to reduce the gain of the amplifier circuit, thereby reducing the signal strength and bringing it back to the normal detection range. Conversely, when the DC signal value is 0.3V, the signal strength is lower than the minimum value of the second range (0.5V), indicating that the signal may be too weak, the detection circuit will also transmit the DC signal value to the gain control circuit. In this case, the gain control circuit generates a gain control signal to increase the gain of the amplifier circuit, thereby increasing the signal strength and ensuring reliable detection by the system.

[0076] In this embodiment, the cooperation between the detection circuit and the gain control circuit can effectively prevent the signal from saturating due to being too strong or being difficult to detect due to being too weak, thus ensuring the linearity and signal-to-noise ratio of signal processing. Real-time gain adjustment and signal strength monitoring enhance the stability of the system, reduce system failures caused by signal strength fluctuations, and improve the reliability of the equipment.

[0077] In one exemplary embodiment, an amplifier circuit is used to amplify the echo signal according to an initial gain of the amplifier circuit to obtain an amplified initial echo signal.

[0078] The echo signal is a laser echo signal received by the detector and converted into an electrical signal, i.e., a signal after photoelectric conversion. The amplified initial echo signal can be the echo signal amplified using an initial gain. It should be noted that each echo signal needs to be initially amplified by an amplification circuit. The amplified initial echo signal can be detected by a detection circuit. If the signal detection result indicates that the gain of the amplification circuit does not need to be adjusted, the signal can be directly sent to the sampling module.

[0079] The initial gain can be a pre-set amplification factor for the amplifier circuit when receiving the echo signal. Optionally, it can be an initial amplification factor value preset for the signal processing system of the lidar. Alternatively, it can be a preset gain table generated based on prior experiments, which includes the correspondence between multiple preset signal average strengths and preset initial gains. The average signal strength is a quantification of the average strength of the echo signal over a certain time or period, used to evaluate the average energy level of the signal. In practice, when the amplifier circuit receives the echo signal, the initial gain corresponding to the average signal strength of the echo signal is determined according to the preset gain table based on the average signal strength of the echo signal. The echo signal is then amplified using the initial gain to obtain the amplified echo signal. It should be noted that if the preset gain table does not contain an initial gain corresponding to the average signal strength of the echo signal, the initial gain can be calculated using linear interpolation.

[0080] In this embodiment, based on the amplifier circuit receiving the echo electrical signal from the detector, the signal is amplified according to its initial gain parameters. This process enhances the originally weak electrical signal to a level more suitable for subsequent circuit processing, ensuring the detectability and sampleability of the signal.

[0081] In one exemplary embodiment, Figure 5 This is a structural block diagram of another optional LiDAR signal processing system according to an embodiment of this application, wherein a set of sampling modules includes a first sampling module, a second sampling module, and a third sampling module;

[0082] The first sampling module is used to sample the first sub-signal in the amplified echo signal whose frequency range is within a preset frequency range;

[0083] The second sampling module is used to sample the second sub-signal in the amplified echo signal whose frequency is greater than the maximum value of the preset frequency range;

[0084] The third sampling module is used to sample the third sub-signal in the amplified echo signal whose frequency is less than the minimum value of the preset frequency range.

[0085] It should be noted that a set of sampling modules can contain multiple sampling modules. Optionally, a set of sampling modules may include a first sampling module, a second sampling module, and a third sampling module. The first sampling module is suitable for signals within a preset frequency range, which is a frequency band predetermined based on signal characteristics to ensure optimal signal processing within this range. The second sampling module can be used to process signals higher than the maximum value of the preset frequency range, i.e., high-frequency signals, to meet the dynamic changes in signal frequency bands. The third sampling module can be used to process signals lower than the minimum value of the preset frequency range, i.e., low-frequency signals, also meeting the processing requirements for frequency band changes. The maximum and minimum values ​​of the preset frequency range are determined based on a series of experiments, specifically based on the operational requirements of the lidar, the hardware performance of various components in the signal processing system, and different application scenarios.

[0086] The first sub-signal can refer to a sub-signal whose frequency range is within a preset frequency range; the second sub-signal can refer to a sub-signal that is higher than the maximum value of the preset frequency range; and the third sub-signal can refer to a sub-signal that is lower than the minimum value of the preset frequency range.

[0087] This embodiment ensures that each signal frequency band is converted under optimal sampling conditions by appropriately matching the sampling modules corresponding to sub-signals in different frequency ranges, thus avoiding data distortion caused by insufficient or inappropriate sampling frequency. Automatically selecting the sampling module based on the signal's frequency characteristics avoids unnecessary signal processing and conversion steps, improving the overall efficiency and speed of signal processing.

[0088] In one exemplary embodiment, the first sampling module includes a first sampling circuit;

[0089] The first sampling circuit is used to perform analog-to-digital conversion on the first sub-signal, and to perform correction processing on the first sub-signal after analog-to-digital conversion through a first preset correction model or a first preset table to obtain the first sub-signal after correction processing. The first preset correction model is used to correct the nonlinear distortion that occurs when the first sub-signal is converted from analog to digital in the first sampling circuit. The first preset table is used to record a set of preset signals and the correction signal corresponding to each preset signal in the set of preset signals.

[0090] It should be noted that the first sub-signal refers to a signal whose frequency range falls within a preset frequency range. The first sub-signal may include the light signal reflected from the target and noise. The first sampling module may include a first sampling circuit, which, as the core component of the first sampling module, is responsible for converting the first sub-signal from an analog signal to a data signal, so as to efficiently and accurately capture the instantaneous information of the signal subsequently. Analog-to-digital conversion can convert the first sub-signal, which is in analog signal form, into a digital signal form.

[0091] The first preset calibration model can be a machine learning model used to correct potential nonlinear distortions in the parameters of the first sampling circuit during analog-to-digital conversion. Through this first preset calibration model, nonlinear effects during signal conversion can be accurately compensated, restoring the original characteristics of the signal. The first preset calibration model can be obtained by performing a series of tests on the selected first sampling circuit. Specifically, refer to... Figure 6 , Figure 6 This is a structural block diagram of another optional test system according to an embodiment of this application. The test system includes an arbitrary waveform generator, a first sampling circuit, and a sampling analysis and correction unit. The sampling analysis and correction unit is closely connected to the sampling circuit via a digital interface, recording and capturing the digital signal output by the sampling circuit in real time. Simultaneously, the sampling analysis and correction unit also maintains communication with the arbitrary waveform generator via another digital interface, precisely controlling the input signal of the circuit under test.

[0092] The sampling analysis corrector generates a first preset correction model using a neural network algorithm. This process is based on a comparative analysis of the original input signal and the output signal of the first sampling circuit, achieving accurate capture and correction of the nonlinear characteristics of the sampling circuit. The following is an overview of this generation process:

[0093] The sampling analysis corrector collects a large amount of comparative data between the original input signal and the corresponding sampling circuit output signal. This comparative data covers a wide range of parameters such as frequency and amplitude, ensuring that the mapping relationship comprehensively reflects the nonlinear characteristics of the sampling circuit. The collected data is divided into a training set and a validation set. The training set is used to build and train a first-preset correction model, while the validation set is used to evaluate the model's accuracy and generalization ability. Appropriate neural network types, such as Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), or Long Short-Term Memory (LSTM), are selected based on the nonlinear characteristics of the sampling circuit. The original input signal is used as the training dataset and input into the selected model; the digital signal output by the sampling circuit is used as the result set. The mapping relationship between the training dataset and the result set is learned through the selected model. Through an iterative optimization process, its internal parameters are adjusted to minimize the error between the input signal and the predicted output signal. The validated data is used to evaluate the trained model to further adjust the model parameters or optimize the neural network architecture to improve the model's accuracy and stability. In practical applications, the nonlinear characteristics of the sampling circuit may undergo slight changes due to environmental variations, equipment aging, etc. Therefore, the first preset calibration model needs to be updated and calibrated regularly using the latest data to ensure the long-term accuracy and stability of the model.

[0094] Similar to the calibration model, the first preset table records a series of preset signals and their corresponding calibration signals. It is a calibration method in the form of a look-up table (LUT). When a specific signal is received, the system can find the most suitable calibration signal through the look-up table to eliminate nonlinear distortion.

[0095] In this embodiment, the first sampling circuit can effectively correct nonlinear distortion during analog-to-digital conversion using a first preset correction model or a first preset table, significantly improving the accuracy and reliability of the signal. The introduction of the correction mechanism enhances the system's robustness; even when signal strength and frequency characteristics change, the preset correction strategy can maintain the stability and consistency of signal processing.

[0096] In one exemplary embodiment, specifically, reference is made to... Figure 7 , Figure 7 This is a structural block diagram of an optional second sampling module according to an embodiment of this application. The second sampling module includes a resonant circuit, a mixer circuit, a filter circuit, and a second sampling circuit. The mixer circuit is connected to the detector circuit, the resonant circuit, and the filter circuit, respectively. The filter circuit is connected to the second sampling circuit.

[0097] A resonant circuit is used to send a preset resonant signal to the mixer circuit when the mixer circuit receives the second sub-signal.

[0098] The mixing circuit is used to receive the second sub-signal and the preset resonant signal, perform mixing processing on the second sub-signal and the preset resonant signal to obtain the mixing signal corresponding to the second sub-signal, and send the mixing signal to the filtering circuit.

[0099] The filtering circuit is used to perform low-pass filtering on the mixing signal and send the filtered signal obtained by low-pass filtering to the second sampling circuit.

[0100] The second sampling circuit is used to perform analog-to-digital conversion on the filtered signal and to correct the filtered signal after analog-to-digital conversion using a second preset correction model or a second preset table to obtain a corrected filtered signal. The second preset correction model is used to correct the nonlinear distortion that occurs when the filtered signal is converted from analog to digital in the second sampling circuit. The second preset table is used to record a set of preset signals and the correction signal corresponding to each preset signal in the set of preset signals.

[0101] The second sub-signal refers to a signal whose frequency range exceeds the preset frequency range of the first sampling circuit. The second sub-signal may include the optical signal reflected from the target and noise. The second sampling module may include a resonant circuit, a mixer circuit, a filter circuit, and a second sampling circuit; the mixer circuit is connected to the detector circuit, the resonant circuit, and the filter circuit, respectively, and the filter circuit is connected to the second sampling circuit.

[0102] A resonant circuit can generate a strong signal response at a specific frequency, used to generate a preset resonant signal. The preset resonant signal can be a signal with a fixed frequency generated by the resonant circuit. In physical implementation, a stable preset resonant signal can be generated using a crystal oscillator or other oscillation source. The frequency of the preset resonant signal can be determined based on the frequency of the signal to be transferred and a preset low-frequency band.

[0103] The preset resonant signal can be used for mixing with the second sub-signal. A low-pass filter removes high-frequency components from the mixed signal, retaining only the low-frequency signal, ensuring the signal frequency falls within the processing range of the second sampling circuit. The second sampling circuit performs analog-to-digital conversion on the filtered signal, converting it into a digital signal for subsequent processing. Analog-to-digital conversion refers to converting an analog signal into a digital signal.

[0104] The second preset correction model can be used to correct the nonlinear distortion of the filtered signal during analog-to-digital conversion in the second sampling circuit; the second preset table can be used to record a set of preset signals and the correction signal corresponding to each preset signal in the set of preset signals. The filtered signal after analog-to-digital conversion is corrected according to the second preset correction model or the second preset table. The generation process of the second preset correction model can refer to the generation process of the first preset correction model; similarly, the generation process of the second preset table can also refer to the generation process of the first preset table, which will not be elaborated upon here. In practice, sampling circuits of the same type of component can be selected as sampling circuits for different sampling modules. Therefore, the first preset correction model and the second preset correction model can be the same model or different models. Similarly, the first preset table and the second preset table can be the same table or different tables.

[0105] It should be noted that the second sampling module can be used to process signals higher than the maximum value of the preset frequency range, i.e., high-frequency signals. In the second sampling module, the high-frequency band can be shifted to a lower frequency accordingly. Similarly, the third sampling module can include a resonant circuit, a mixer circuit, a filter circuit, and a third sampling circuit. The processing methods for the third sub-signal in the resonant circuit, mixer circuit, filter circuit, and third sampling circuit can refer to those in the second sampling module. Of course, the third sampling module can also be used to process signals lower than the minimum value of the preset frequency range, i.e., low-frequency signals. In this case, a high-pass filter is used in the filter circuit of the third sampling module to shift the low-frequency band to a higher frequency accordingly.

[0106] In this embodiment, the second sampling module may include a mixing module and a filtering module. These modules process signals whose frequencies exceed a preset range, converting them to a lower frequency band. This ensures the signal can be effectively detected and processed, expanding the spectral adaptability of the lidar system. Furthermore, low-pass filtering and nonlinear correction ensure accurate signal conversion over a wide bandwidth, reducing signal distortion and improving signal processing precision.

[0107] In one exemplary embodiment, the mixing circuit is further configured to multiply the second sub-signal and the preset resonant signal to obtain a mixed signal, wherein the mixed signal includes at least one of the following frequency signals: a difference frequency signal and a sum frequency signal; the frequency of the difference frequency signal is the frequency difference between the frequency of the second sub-signal and the frequency of the preset resonant signal, and the frequency of the sum frequency signal is the sum of the frequencies of the second sub-signal and the preset resonant signal.

[0108] The mixer circuit, used in the signal processing system for frequency conversion, generates a mixed signal by multiplying the second sub-signal by a preset resonant signal. The mixed signal can include a difference frequency signal or a sum frequency signal, and its frequency characteristics are adjusted to suit the processing capabilities of the second sampling circuit. After processing by the mixer circuit, a new signal is generated based on the frequency difference or sum of the second sub-signal and the preset resonant signal. The frequency of the difference frequency signal is the frequency difference between the frequencies of the second sub-signal and the preset resonant signal, and the frequency of the sum frequency signal is the sum of the frequencies of the second sub-signal and the preset resonant signal.

[0109] Specifically, the main component in a mixing circuit is the mixer, a three-terminal device with two inputs and one output. Its working principle is to multiply two signals of different frequencies to generate a new frequency signal. These new frequency signals are the sum and difference of the original two frequency signals.

[0110] The angular frequency of the local oscillator is set to ω0, and the angular frequency of the second sub-signal is set to ω1. Their time-domain signal expressions are shown in Equation (1) and Equation (2) respectively:

[0111]

[0112] Where A0 is the amplitude of the preset resonant signal, and A1 is the amplitude of the second sub-signal. The initial phase of the preset resonant signal, This is the initial phase of the second sub-signal.

[0113] The output z(t) of the mixer is the product of the two input signals, as shown in formula (3):

[0114] z(t) = x(t) * y(t);

[0115] Substituting the expressions for x(t) and x(t) into the above equation, we get:

[0116]

[0117] Simplify the above expression using the product formula of trigonometric functions (sum-to-product formula):

[0118]

[0119] Will and Substituting into the above equation, we get:

[0120]

[0121] As can be seen from the above formula, the output of the multiplier includes a difference frequency signal and a sum frequency signal:

[0122] Components of the sum-frequency signal: Its frequency is ω0+ω1.

[0123] Components of the difference frequency signal: Its frequency is ω0-ω1.

[0124] If the amplitude of the second sub-signal is A2 at this time, and the overall gain of the mixer link and filter is G1, then its relationship with the amplitude of the original signal A1 is as follows:

[0125]

[0126] Therefore, it can be deduced that:

[0127]

[0128] Where A0 is the amplitude of the preset resonant signal, A1 is the original amplitude of the second sub-signal, and A2 is the current amplitude of the second sub-signal.

[0129] In this embodiment, the mixer circuit can process signals whose frequencies exceed the preset range. By frequency conversion, the signal frequency is adapted to the working range of the second sampling circuit, avoiding the problem that high-frequency signals cannot be accurately detected and processed, and improving the frequency adaptability and flexibility of the lidar system.

[0130] To better understand the process of processing sub-signals of different frequency bands separately in the embodiments of this application, an example is provided. Specifically, refer to... Figure 8 , Figure 8 This is a structural block diagram of another optional LiDAR signal processing system in the embodiments of this application. The LiDAR signal processing system may include a detector, an amplifier circuit, a detector circuit, a gain control circuit, a first sampling module, a second sampling module, and a third sampling module. The first sampling module includes a sampling circuit 1, the second sampling module includes a resonant circuit 1, a mixer circuit 1, a filter circuit 1, and a sampling circuit 2, and the third sampling module includes a resonant circuit 2, a mixer circuit 2, a filter circuit 2, and a sampling circuit 3.

[0131] In the signal processing system of a lidar, the frequency range of the amplified echo signal detected by the detection circuit is 5MHz to 45MHz. The frequency of the signal processed by the first sampling module is between 15MHz and 25MHz, exhibiting good linearity. Therefore, the detection circuit can divide the amplified echo signal with a frequency range of 5MHz to 45MHz into multiple sub-signals. Alternatively, a frequency range can be set for each sampling module, allowing only signals belonging to that frequency range to pass. The frequency range corresponding to each sub-signal can be 5MHz to 15MHz, 15MHz to 25MHz, or 25MHz to 45MHz. A preset resonant signal with a frequency of 10MHz or a multiple thereof can be selected for mixing.

[0132] In the first sampling module, no mixing operation is required. The sampling circuit 1 in the first sampling module directly performs analog-to-digital conversion and correction processing on the sub-signals with a frequency range of 15MHz to 25MHz.

[0133] In the second sampling module, when the mixing circuit 1 receives a sub-signal with a frequency range of 25MHz to 45MHz, the resonant circuit 1 sends a preset resonant signal of 20MHz to the mixing circuit 1. The mixing circuit 1 mixes the sub-signal with a frequency range of 25MHz to 45MHz and the preset resonant signal of 20MHz to obtain a mixed signal corresponding to the sub-signal with a frequency range of 25MHz to 45MHz, and sends the mixed signal corresponding to the sub-signal with a frequency range of 25MHz to 45MHz to the filtering circuit 1. The filtering circuit 1 performs low-pass filtering on the mixed signal corresponding to the sub-signal with a frequency range of 25MHz to 45MHz, and sends the filtered signal obtained from the low-pass filtering to the second sampling circuit, thus realizing the transfer of information from the high-frequency band to the low-frequency band. Then, the sampling circuit 2 in the second sampling module performs analog-to-digital conversion and correction processing on the signal transferred from the high-frequency band to the low-frequency band.

[0134] In the third sampling module, when the mixing circuit 2 receives a sub-signal with a frequency range of 15MHz to 25MHz, the resonant circuit 2 sends a preset resonant signal of 10MHz to the mixing circuit 2. The mixing circuit 2 mixes the sub-signal with a frequency range of 15MHz to 25MHz and the preset resonant signal of 10MHz to obtain a mixed signal corresponding to the sub-signal with a frequency range of 15MHz to 25MHz, and sends the mixed signal corresponding to the sub-signal with a frequency range of 15MHz to 25MHz to the filtering circuit 2. The filtering circuit 2 performs high-pass filtering on the mixed signal corresponding to the sub-signal with a frequency range of 15MHz to 25MHz, and sends the filtered signal obtained from the high-pass filtering to the second sampling circuit, thus realizing the transfer of information from the low-frequency band to the high-frequency band. Then, the sampling circuit 3 in the third sampling module performs analog-to-digital conversion and correction processing on the signal transferred from the low frequency to the high frequency band.

[0135] Specifically, the number of sampling modules in the signal processing system of a lidar can be greater than 3. Specifically, sampling modules that can be added from high frequency to low frequency or from low frequency to high frequency can be added based on the requirements. Furthermore, the frequency ranges that each sampling module can process can overlap to a certain extent. Specifically, when the frequency range of the signal processed by the first sampling module is 15MHz to 25MHz, the frequency of the signal processed by the second sampling module can be 8MHz to 18MHz.

[0136] It should be noted that the sampling circuits in different sampling modules can be the same or different. That is, after spectrum shifting, the frequency range after spectrum shifting should all meet the sampling frequency requirements of the first sampling circuit, so that the first sampling circuit can be used for sampling in all of them. Of course, each sampling module can also use a different sampling circuit to achieve parallel sampling.

[0137] In practical application, when constructing a LiDAR signal processing system, it is necessary to consider the system noise of the sampled signal generated by the signal processing system and determine the statistical characteristics of the system noise, including but not limited to key parameters such as the noise mean and variance. When a standard signal is input to the system, the differences between the digital signal output from the sampling link and the input standard signal in the time and frequency domains are compared. This comparison not only reveals how the signal changes after passing through the system, such as the shift or distortion of basic information like frequency, amplitude, and phase, but also guides the optimization of the circuit's linear range by adjusting parameters such as circuit gain and impedance. Specifically, refer to... Figure 9 , Figure 9This is a schematic diagram illustrating an optional comparison of a standard signal and a sampled signal in an embodiment of this application. A standard signal is input into the detector, and the standard signal is processed sequentially through the detector, an amplifier circuit, and a sampling circuit to obtain a sampled signal. The standard signal and the sampled signal are then compared. By comparing the standard signal and the sampled signal, the distortion introduced by the amplifier circuit and the sampling circuit can be evaluated, providing a basis for the nonlinear correction loop.

[0138] It should be noted that this application considers improving the amplifier circuit by selecting appropriate components when designing the detection and gain control circuits. Similarly, it also modifies the detector and sampling circuit by testing different components. Specifically, the selection of the detector is mainly based on its key performance indicators such as photoelectric conversion efficiency, dark current, and dynamic range. Dark current, which is the detector's current when there is no light signal input, has a direct impact on system noise. Therefore, selecting a detector with low dark current can effectively reduce system noise. The detector's dynamic range should match the operating environment of the lidar to ensure effective operation under different lighting conditions. For example, under high illumination conditions, the detector needs to have a high saturation current to avoid signal distortion due to excessive intensity; under low illumination or long-distance detection conditions, the detector needs to have high sensitivity to detect weak signals.

[0139] When optimizing the gain range of an amplifier circuit, the relationship between system noise and signal dynamic range should be considered. Excessive gain may lead to signal saturation, while insufficient gain may cause the signal to be submerged in noise. Therefore, an optimal balance needs to be found between signal distortion and signal-to-noise ratio (SNR) to ensure high linearity and SNR within the optimal gain range. Specifically, different scenarios are used to determine the maximum and minimum amplitudes of the signal, as well as the lower and upper limits of the quantizer input range. The gain adjustment range is then determined based on these scenarios and the lower and upper limits of the quantizer input range. The gain adjustment range is adjusted according to a preset accuracy step size to obtain an optimal gain range that minimizes signal distortion while ensuring sufficient signal strength to meet the requirements of the sampling circuit. Outside the optimal gain range, signals can still be detected, but linearity is poor; therefore, it is generally not recommended as the primary observation range unless absolutely necessary.

[0140] The performance of a sampling circuit is affected by the quantization interval (the effective input range of the quantizer) and the number of quantization bits. A higher number of quantization bits results in lower quantization noise, but also increases cost and complexity. The quantization interval should cover the dynamic range of the signal, but it should not be too wide to avoid excessive quantization noise. When determining the quantization interval and number of bits for the sampling circuit, the maximum and minimum amplitudes of the signal, as well as the system noise level, must be considered. The effective value of the quantization noise is typically related to the number of bits and the full-scale range of the ADC. Specifically, the effective number of bits is calculated using the following formula:

[0141]

[0142] Where ENOB is the effective number of bits, FSR is the full-scale range, which refers to the maximum range of input signals that the ADC can measure; NAD is the effective noise value, which refers to the noise power density of the ADC output when the input signal is zero; N is the number of bits of the ADC; ε Q It is the root mean square of the ideal quantization noise.

[0143] Choosing an appropriate quantization bit depth can satisfy the accuracy requirements of signal processing while controlling the system's cost and complexity.

[0144] In the field of electronic signal processing, the relationship between system noise and signal distortion is a crucial factor affecting signal quality and system performance. System noise not only degrades signal quality but can also introduce additional distorted signal energy, leading to signal distortion. To quantify this relationship, Total Harmonic Distortion Plus Noise (THD+N) is used as a key indicator. THD+N integrates harmonic distortion and noise effects, expressed as the ratio of distorted signal energy to the original signal energy, usually presented as a percentage. The calculation of THD+N involves the ratio of the root mean square value of the fundamental signal to the sum of the root mean square values ​​of harmonic energy and noise energy, reflecting the impact of system noise and distortion on the overall signal quality. Specific quantification methods include: using an arbitrary waveform generator to input a pure sine wave at the system input; the signal is then affected by noise and distortion in the system, and the output signal is no longer a pure sine wave; in addition to the fundamental frequency (f), a series of higher harmonics with frequencies that are integer multiples of the fundamental frequency will appear. By measuring the harmonic energy and noise energy of the output signal and comparing them with the fundamental energy of the input signal, the THD+N value can be calculated, thereby assessing the impact of system noise and distortion on signal quality.

[0145] There is a certain proportional relationship between system noise and quantization noise, and the quantization standard can be defined by the signal-to-noise ratio (SNR). An SNR threshold T can be determined through experimental testing. When the ratio of system noise power to quantization noise power (SNR) is greater than T, the influence of quantization noise can be considered negligible. In practice, the system noise level can be gradually adjusted, and the SNR and signal quality monitored until a point is found where the influence of quantization noise becomes insignificant. This process involves precise control of system noise, typically requiring the use of a nonlinear correction loop to ensure that the ratio of noise to quantization noise meets design requirements under different gain settings.

[0146] It should be noted that the above modules 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 modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0147] 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.

[0148] Obviously, those skilled in the art should understand that the modules or steps of this application 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 presented here, 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, this application is not limited to any particular combination of hardware and software.

[0149] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A signal processing system for a lidar, characterized in that, The signal processing system includes a detector, an amplification module, and a sampling module. The amplification module includes an amplification circuit and a nonlinear correction loop. The sampling module includes a set of sampling modules. The detector is connected to the amplification circuit, and the amplification module is connected to the sampling module. The detector is used to receive the laser echo signal reflected by the target, convert the laser echo signal from an optical signal into an echo electrical signal, and send the converted echo electrical signal to the amplifier circuit. The amplification circuit is used to amplify the echo signal according to the gain control signal sent by the nonlinear correction loop, and send the amplified echo signal to the nonlinear correction loop. The nonlinear correction loop is used to perform signal detection processing on the amplified echo signal to obtain a signal detection result, adjust the gain control signal according to the signal detection result and send it to the amplification circuit; and detect the first spectral characteristics of the amplified echo signal. The sampling module is used to receive the first spectral characteristics provided by the nonlinear correction loop, select a sampling module from the group of sampling modules according to the first spectral characteristics, and sample the amplified echo signal through the selected sampling module; wherein, the multiple sampling modules in the sampling module correspond to different spectral ranges.

2. The system according to claim 1, characterized in that, The nonlinear correction loop includes a detection circuit and a gain control circuit. The amplification circuit is connected to both the detection circuit and the gain control circuit. The detection circuit is connected to both the gain control circuit and the sampling module. The detection circuit is used to perform signal detection processing on the amplified echo electrical signal, obtain the signal detection result, and send the signal detection result to the gain control circuit. The gain control circuit is used to generate the gain control signal based on the signal detection result and send the gain control signal to the amplification circuit, wherein the gain control signal is used to indicate the amplification factor of the amplification circuit.

3. The system according to claim 2, characterized in that, The detection circuit is used to perform envelope detection on the amplified echo signal to obtain signal envelope parameter values, wherein the signal envelope parameter values ​​include at least one of the following: envelope variance, envelope peak-to-peak value, and envelope mean value; the signal detection result includes the signal envelope parameter values; and the signal envelope parameter values ​​are sent to the gain control circuit. The gain control circuit is used to generate the gain control signal based on the signal envelope parameter value.

4. The system according to claim 2, characterized in that, The detection circuit is used to perform spectrum analysis on the amplified echo signal to obtain a second spectral characteristic, and send it to the gain control circuit, wherein the signal detection result includes the second spectral characteristic; The gain control circuit is used to generate the gain control signal based on the second spectral characteristics.

5. The system according to claim 2, characterized in that, The detection circuit is used to rectify and low-pass filter the amplified echo signal to obtain the DC signal value of the amplified echo signal, and send the DC signal value to the gain control circuit. The signal detection result includes the DC signal value, which is used to represent the average intensity of the amplified echo signal. The gain control circuit is used to generate the gain control signal based on the DC signal value.

6. The system according to claim 2, characterized in that, The amplifier circuit is used to amplify the echo signal according to the initial gain of the amplifier circuit to obtain the amplified initial echo signal.

7. The system according to claim 2, characterized in that, The set of sampling modules includes a first sampling module, a second sampling module, and a third sampling module; The first sampling module is used to sample the first sub-signal in the amplified echo signal whose frequency range is within a preset frequency range; The second sampling module is used to sample the second sub-signal in the amplified echo signal whose frequency is greater than the maximum value of a preset frequency range; The third sampling module is used to sample the third sub-signal in the amplified echo signal whose frequency is less than the minimum value of a preset frequency range.

8. The system according to claim 7, characterized in that, The first sampling module includes a first sampling circuit; The first sampling circuit is used to perform analog-to-digital conversion on the first sub-signal, and to perform correction processing on the first sub-signal after analog-to-digital conversion through a first preset correction model or a first preset table to obtain the first sub-signal after correction processing. The first preset correction model is used to correct the nonlinear distortion that occurs when the first sub-signal is converted from analog to digital in the first sampling circuit. The first preset table is used to record a set of preset signals and a correction signal corresponding to each preset signal in the set of preset signals.

9. The system according to claim 7, characterized in that, The second sampling module includes a resonant circuit, a mixer circuit, a filter circuit, and a second sampling circuit; the mixer circuit is connected to the detector circuit, the resonant circuit, and the filter circuit, respectively, and the filter circuit is connected to the second sampling circuit; wherein, The resonant circuit is used to send a preset resonant signal to the mixing circuit when the mixing circuit receives the second sub-signal; The mixing circuit is used to receive the second sub-signal and the preset resonant signal, perform mixing processing on the second sub-signal and the preset resonant signal to obtain the mixing signal corresponding to the second sub-signal, and send the mixing signal to the filtering circuit; The filtering circuit is used to perform low-pass filtering on the mixing signal and send the filtered signal obtained by low-pass filtering to the second sampling circuit. The second sampling circuit is used to perform analog-to-digital conversion on the filtered signal, and to perform correction processing on the filtered signal after analog-to-digital conversion through a second preset correction model or a second preset table to obtain the corrected filtered signal. The second preset correction model is used to correct the nonlinear distortion that occurs when the filtered signal is converted from analog to digital in the second sampling circuit. The second preset table is used to record a set of preset signals and the correction signal corresponding to each preset signal in the set of preset signals.

10. The system according to claim 9, characterized in that, The mixing circuit is further configured to multiply the second sub-signal and the preset resonant signal to obtain the mixed signal, wherein the mixed signal includes at least one of the following frequency signals: a difference frequency signal and a sum frequency signal; the frequency of the difference frequency signal is the frequency difference between the frequency of the second sub-signal and the frequency of the preset resonant signal, and the frequency of the sum frequency signal is the sum of the frequencies of the second sub-signal and the preset resonant signal.

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