Laser pulse width and integral window weak coupling flight time measurement system and method

Abstract

The invention discloses a laser pulse width and integral window weak coupling flight time measurement system and method, and belongs to the technical field of single photon detection and integrated circuits. The method comprises the following steps: receiving single photon trigger event signals from SPAD pixels in a measurement interval, discretizing and counting the single photon trigger event signals to obtain global histogram data of the whole measurement interval, determining peak position information based on the global histogram data, determining histogram data of effective sub-intervals based on the peak position information, and calculating the single photon trigger event signals according to the histogram data of the effective sub-intervals. And carrying out differentiation recombination and linear combination operation on the histogram data to obtain an echo rising edge time index, generating complete flight time based on the initial index of the effective subinterval, the echo rising edge time index and an indirect flight time calculation formula, and converting the complete flight time into the target depth. According to the invention, the strong coupling limitation that the laser pulse width and the integral window need to be strictly matched in the traditional indirect time-of-flight technology is broken through, and high-precision distance measurement can be realized under the conditions of strong background light and wide dynamic range.

Description

Technical Field

[0001] This invention belongs to the field of single-photon detection and integrated circuit technology, specifically relating to a time-of-flight measurement system and method with weak coupling between laser pulse width and integration window. Background Technology

[0002] Time-of-flight (TOF) ranging technology is the core technology of lidar based on single-photon avalanche diodes (SPADs). Its principle is to calculate the target distance by measuring the round-trip time of a light pulse, providing fundamental technical support for ranging scenarios. Existing TOF extraction algorithms mainly include direct TOF and indirect TOF methods. Direct TOF methods accumulate and statistically analyze the photon arrival distribution, construct a histogram, and extract peak positions to directly obtain the flight time. This allows for a wide measurement range and is suitable for long-distance measurements; however, its measurement accuracy is highly dependent on the time-to-digital conversion circuit. As accuracy requirements increase, the size of the histogram storage unit also increases significantly, increasing resource consumption and system complexity. Indirect TOF methods obtain the flight time by measuring the phase difference between the emitted light pulse and the echo. This method has high measurement accuracy, but its dynamic ranging range is limited, making it unsuitable for wide-range ranging scenarios. Therefore, combining these two methods can balance the dynamic range and measurement accuracy of ranging, meeting the comprehensive application requirements of high precision, wide dynamic range, and low resource consumption. In addition, existing indirect time-of-flight extraction algorithms have technical limitations: the constraint that the laser pulse width and the integral window (bin) must be matched limits the ranging dynamic range and photon counting efficiency, reducing the applicability and robustness of the system in complex environments.

[0003] In other words, how to achieve a balance between a wide measurement range and high-precision time resolution, and how to break through the traditional indirect time-of-flight dependence of strict matching of laser pulse width and integration window, is a problem that urgently needs to be solved. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, this invention provides a time-of-flight measurement system and method with weak coupling between laser pulse width and integration window.

[0005] The technical problem to be solved by this invention is achieved through the following technical solution: This invention provides a time-of-flight measurement system with weak coupling between laser pulse width and integration window, comprising: The histogram statistics algorithm module is used to receive single-photon trigger event signals from SPAD pixels in each preset measurement cycle, and to discretize and statistically analyze the single-photon trigger event signals until the end of the last preset measurement cycle to obtain global histogram data for the entire measurement interval. The histogram data is the number of trigger events in each integration window within P consecutive integration windows, and each integration window corresponds to a storage address. The echo photon positioning module is used to determine peak position information based on the global histogram data, and to determine the histogram data of the effective sub-interval based on the peak position information, thereby obtaining local histogram data. The effective sub-interval has a starting index, and the local histogram data is the number of trigger events of each integration window within K consecutive integration windows, where K and P are both positive integers greater than 0, and K is less than P. The echo feature analysis module is used to perform structured processing on the local histogram data through differentiation, recombination and linear combination operations to obtain the echo rise time index. The time-of-flight calculation module is used to generate a complete time of flight based on the starting index of the effective sub-interval, the rising edge time index of the echo, and the indirect time-of-flight calculation formula, and to convert the complete time of flight into the target depth.

[0006] This invention also provides a time-of-flight measurement method with weak coupling between laser pulse width and integration window, comprising: In each preset measurement cycle, a single-photon trigger event signal from the SPAD pixel is received, and the single-photon trigger event signal is discretized and statistically analyzed until the last preset measurement cycle ends to obtain the global histogram data of the entire measurement interval. The histogram data is the number of trigger events in each integration window within P consecutive integration windows, and each integration window corresponds to a storage address. Based on the global histogram data, peak position information is determined, and based on the peak position information, histogram data of effective sub-intervals is determined to obtain local histogram data. The effective sub-intervals have starting indices, and the local histogram data is the number of trigger events of each integration window within K consecutive integration windows. K and P are both positive integers greater than 0, and K is less than P. The local histogram data is structured through differentiation, recombination, and linear combination operations to obtain the echo rise time index. Based on the starting index of the effective sub-interval, the rising edge time index of the echo, and the indirect time-of-flight calculation formula, the complete time of flight is generated and converted into the target depth.

[0007] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention combines histogram statistics with structured indirect time-of-flight feature calculation, maintaining coverage comparable to direct time-of-flight methods in overall detection range, thus breaking the limitation of traditional indirect time-of-flight methods, which are typically only applicable to short-range scenarios. Simultaneously, this invention constructs multiple features within effective sub-intervals and performs rising edge analysis, resulting in significantly higher distance accuracy than direct time-of-flight methods that rely solely on histogram peak detection. Furthermore, by introducing differentiation-recombination and linear combination mechanisms, this invention weakens the dependence of indirect time-of-flight methods on strict matching of laser pulse width and integration window, allowing the laser pulse width to be flexibly set within a range of multiples of the integration window. This ensures good adaptability and robustness under different lighting conditions, reflection characteristics, and working distances, significantly improving the system's engineering usability.

[0008] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of the architecture of a time-of-flight measurement system with weak coupling between laser pulse width and integration window provided in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the generation process of S structured data sequences and S feature values ​​provided in an embodiment of the present invention; Figure 3 It is a schematic diagram of the variation curves of four preset cosine-like curves in a single time period; Figure 4 This is a schematic diagram illustrating the calculation principle of a complete flight time provided in an embodiment of the present invention; Figure 5 This is a flowchart illustrating the time-of-flight measurement method with weak coupling between laser pulse width and integration window provided in an embodiment of the present invention. Detailed Implementation

[0010] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0011] To address the technical contradiction of simultaneously requiring wide dynamic range measurement capabilities and high-precision time-of-flight measurement capabilities, as well as the strong coupling constraint in traditional indirect time-of-flight methods where the laser pulse width must be strictly matched with the integration window, this invention proposes a time-of-flight measurement system and method with weak coupling between the laser pulse width and the integration window. This system can handle photon events output by SPAD arrays of arbitrary size. By constructing an overall processing architecture consisting of a histogram statistical algorithm module, an echo photon localization module, an echo feature analysis module, and a time-of-flight calculation module, this invention achieves end-to-end processing from photon time distribution statistics, effective segment selection, characteristic rising edge extraction to deep fusion calculation, ultimately achieving a balance and optimization between wide dynamic range detection, high-precision analysis, and pulse width flexibility.

[0012] Figure 1 This is a schematic diagram of the architecture of the time-of-flight measurement system with weak coupling between laser pulse width and integration window provided by the present invention. Figure 1 As shown, the time-of-flight measurement system with weak coupling between laser pulse width and integration window provided by the present invention includes: a histogram statistical algorithm module 110, an echo photon localization module 120, an echo feature analysis module 130, and a time-of-flight calculation module 140. The histogram statistical algorithm module 110 receives single-photon trigger event signals from SPAD pixels within each preset measurement cycle, and discretizes and statistically analyzes the single-photon trigger event signals until the end of the last preset measurement cycle, obtaining global histogram data for the entire measurement interval. The histogram data represents the number of trigger events in each integration window within P consecutive integration windows, with each integration window corresponding to a storage address. The echo photon localization module 120 determines peak position information based on the global histogram data and determines the histogram data of the effective sub-interval based on the peak position information, obtaining local histogram data. The effective sub-interval has a starting index, and the local histogram data represents the number of trigger events in each integration window within K consecutive integration windows, where K and P are both positive integers greater than 0, and K is less than P. The echo feature analysis module 130 is used to perform structured processing on the local histogram data through differentiation, recombination, and linear combination operations to obtain the echo rising edge time index. The time-of-flight calculation module 140 is used to generate the complete time of flight based on the starting index of the effective sub-interval, the echo rising edge time index, and the indirect time-of-flight calculation formula, and convert the complete time of flight into the target depth.

[0013] In some embodiments, such as Figure 1 As shown, the histogram statistics algorithm module 110 includes an event receiving unit 1101 and a histogram accumulation unit 1102.

[0014] The event receiving unit 1101 is used to receive single-photon trigger event signals from SPAD pixels within each preset measurement period, and convert each received single-photon trigger event signal into a timestamp. Each preset measurement period covers the entire measurement interval, which is a time interval consisting of P consecutive integration windows. The event receiving unit 1101 includes a synchronous sampling or time-to-digital converter. The event receiving unit 1101 is used to receive single-photon trigger event signals from SPAD pixels within each preset measurement period, and convert each received single-photon trigger event signal into a timestamp using methods such as synchronous sampling and time-to-digital converter, so as to provide a data basis for the statistical operation of the subsequent histogram accumulation unit 1102.

[0015] The histogram accumulation unit 1102 corresponds to P consecutive integration windows, each corresponding to a storage address. The histogram accumulation unit 1102 is used to convert each received timestamp information into a storage address within each preset measurement period, count the current number of trigger events in the integration window corresponding to the storage address, increment the obtained statistical value by one to obtain the latest number of trigger events in the integration window corresponding to the storage address, until the end of the last preset measurement period, obtaining the number of trigger events for each integration window, and using the number of trigger events for each integration window within the P consecutive integration windows as the global histogram data for the entire measurement interval. For example, the histogram accumulation unit 1102 includes a first control circuit, an accumulation circuit, and a storage circuit. The storage circuit corresponds to P consecutive integration windows for storing the complete time distribution histogram within the entire measurement interval via random access. The first control circuit controls address generation, the histogram accumulation process, and the read / write enable and timing of the storage circuit. The accumulation circuit performs read, sum, and write-back accumulation operations on the data at the storage address corresponding to the timestamp information in the storage circuit. Each integration window has the same duration, and both the value of P and the duration of the integration window can be set according to actual needs; this invention does not impose any limitations on this. The first control circuit controls the accumulation circuit and the storage circuit. Within each preset measurement period, whenever a timestamp is received from the event receiving unit 1101, the first control circuit converts the timestamp into a storage address, indicating that a new single-photon triggering event has occurred within the integration window corresponding to that storage address. Then, the accumulation circuit first counts the current number of triggering events within the integration window corresponding to that storage address, and then increments the current count value within the integration window corresponding to that storage address to obtain the latest number of triggering events within the integration window corresponding to that storage address. This process continues until the end of the last preset measurement period, obtaining the number of triggering events for each integration window, and using the number of triggering events for each of these P consecutive integration windows as the global histogram data for the entire measurement interval.

[0016] In some embodiments, such as Figure 1 As shown, the echo photon localization module 120 includes a peak detection unit 1201 and an interval truncation unit 1202. The peak detection unit 1201 determines the maximum number of events from P consecutive integration windows corresponding to P trigger event counts, and uses the storage address of the integration window corresponding to the maximum number of events as the peak position information. By analyzing global histogram data, the peak detection unit 1201 can initially locate the approximate interval of the echo. For example, the peak detection unit 1201 includes a comparison circuit and a buffer circuit, and the initial value in the buffer circuit is 0. The P consecutive integration windows generated by the histogram accumulation unit 1102, each corresponding to one of the P trigger event counts, are transmitted sequentially to the comparison circuit according to the order of the storage addresses corresponding to the integration windows. The comparison circuit compares each received trigger event count with the value pre-stored in the cache circuit. If the received trigger event count is greater than the current value stored in the cache circuit, the received trigger event count replaces the current value in the storage circuit, and the storage address of the integration window to which the received trigger event count belongs replaces the storage address of the current value in the storage circuit. This process continues until the comparison of the last received trigger event count is completed. After this, the cache circuit stores the maximum count value and its corresponding storage address. This storage address is the peak position information, which is then transmitted to the interval interception unit 1202. The interval extraction unit 1202 uses the integration window corresponding to the peak position information as the target integration window, and expands the target integration window along the time axis by a preset number of integration windows before and after it to obtain K consecutive integration windows. The number of trigger events in each of the K consecutive integration windows is used as histogram data for the effective sub-interval to obtain local histogram data. The storage address of the first integration window in the K consecutive integration windows is used as the starting index of the effective sub-interval. The local histogram data is transmitted to the echo feature analysis module 130, and the starting index of the effective sub-interval is transmitted to the time-of-flight calculation module 140. This effective sub-interval serves as the processing range for subsequent echo phase feature analysis, completely covering the effective information of the target echo. This design excludes invalid data generated by background triggers from the processing path of the echo feature analysis module 130. In summary, the effective sub-interval not only reduces the participation of invalid background data but also provides targeted, highly relevant data input for the subsequent echo feature analysis module 130.

[0017] In some embodiments, such as Figure 1 As shown, the echo feature analysis module 130 includes: a histogram differentiation and recombination unit 1301, a difference and feature combination unit 1302, and a rising edge determination unit 1303.

[0018] The histogram differentiation and recombination unit 1301 is used to divide the number of K trigger events corresponding to K consecutive integration windows into G subgroups according to a preset differentiation and recombination factor S. Each subgroup contains S trigger event counts, where the product of S and G equals K. The trigger event counts in the G subgroups that are at the same sequence position are then recombinated into a structured data sequence, resulting in S structured data sequences. The elements within each structured data sequence are then summed to obtain S feature values ​​corresponding to the S structured data sequences. The value of S can be set according to actual needs, such as 4, 8, 16, etc., and this invention does not limit this. In this invention, the lower limit of the laser pulse width range is the time length of two integration windows, and the upper limit is the time length of S-1 integration windows. For example... Figure 2 This is a schematic diagram illustrating the generation process of S structured data sequences and S feature values. (For example...) Figure 2 As shown, when K=64 and S=8, the number of K trigger events is denoted as {fbin0,fbin1,fbin2,…,fbin63}. Figure 2 (The example only uses 0-63, omitting fbin). Therefore, {fbin0, fbin1, fbin2, ..., fbin63} can be divided into 8 subgroups, namely subgroup 1 to subgroup 8. Subgroup 1 is {fbin0, fbin1, fbin2, ..., fbin7}, subgroup 2 is {fbin8, fbin9, fbin10, ..., fbin15}, subgroup 3 is {fbin16, fbin17, fbin18, ..., fbin23}, and so on. Then, the trigger event counts at the same sequence position in the 8 subgroups are reorganized into a structured data sequence, resulting in 8 structured data sequences Obin0 to Obin7. These 8 structured data sequences are numbered sequentially from 1 to 8. Then, the elements in Obin0 to Obin7 are summed to obtain 8 summation values ​​N0 to N7, each corresponding to one of Obin0 to Obin7. Figure 2(N0~N7 are not shown in the diagram). These 8 summation values ​​are the 8 feature values. For example, by adding fbin0, fbin8, fbin16, fbin24, fbin32, fbin40, fbin48, and fbin56 contained in Obin0, a summation value corresponding to Obin0 can be obtained. For example, the histogram differentiation and recombination unit 1301 includes a second control circuit, a differentiation circuit, a recombination circuit, and a summation circuit. The second control circuit is used to control the execution flow of subgroup division, recombination, and summation. The differentiation circuit is used to preset the differentiation and recombination factor S to divide the K trigger events into subgroups at equal intervals. The recombination circuit is used to rearrange the values ​​of the corresponding sequence positions in each subgroup to form a structured data sequence. The summation circuit is used to perform a summation operation on the data in each structured data sequence to generate feature values ​​and transmit the feature values ​​to the difference and feature combination unit 1302.

[0019] The difference and feature combination unit 1302 is used to perform difference operations sequentially on the feature value sequence composed of S feature values, and to perform L sets of linear combination operations on the feature value sequence after the difference operation using L sets of weight coefficients, to obtain a modulation value sequence containing L modulation values ​​that vary with flight time, where L is... S is a positive integer greater than 1, and both S and L are even numbers. Specifically, the difference and feature combination unit 1302 performs a difference operation on the feature value sequence composed of S feature values ​​to obtain a sequence containing... The difference sequence of L difference values ​​is weighted and summed using each of the L sets of weighting coefficients, resulting in L summed values. Each set of weighting coefficients contains values ​​related to the difference sequence. Each difference value corresponds to one-to-one with There are L weighting coefficients, and L summed values ​​are L modulation values ​​that vary with flight time. These L modulation values ​​constitute a modulation value sequence. Here, the uniformly distributed background noise signal can be suppressed through differential operations. The expression for the i-th differential value Xi is: Xi = (Ni+1) - (Ni-1), where the value of i is... Ni+1 is the (i+1)th eigenvalue in the eigenvalue sequence, and Ni-1 is the (i-1)th eigenvalue in the eigenvalue sequence. For example, the differential and feature combination unit 1302 includes a differential circuit and a linear combination circuit. The differential circuit performs differential operations on the eigenvalue sequence composed of S eigenvalues ​​to suppress common-mode noise. The linear combination circuit uses each of the L sets of weighting coefficients to perform a weighted summation on the differential sequence, resulting in a modulation value sequence composed of L modulation values ​​that vary with flight time, which is then transmitted to the rising edge determination unit 1303. It should be noted that the value of each set of weighting coefficients can be determined based on the ratio of the laser pulse width to the time length of each integration window. This allows the strong coupling relationship between the laser pulse width and the integration window to be converted into a weak coupling relationship. The value of L can be set according to actual needs, and this invention does not limit this.

[0020] For example, each set of weight coefficients corresponds to a preset cosine-like curve, and each set of weight coefficients is determined based on a preset cosine-like curve. The method for determining the L sets of weight coefficients is as follows: S1. Based on the ratio of the laser pulse width to the time length of each integration window, and The phase difference between the change curves of two adjacent difference values ​​in the difference values. Using plotting tools, a curve is generated showing the change of each difference value over a time period. The horizontal axis of the curve represents the ratio of flight time to the time length of each integration window, and the vertical axis represents the number of triggered events. Each time period is... A period is defined by a number of integration windows, and each integration window is a sub-period of that time period. For example, the plotting tools can be MATLAB, Python, etc., and this invention does not limit them.

[0021] Specifically, the ratio of the laser pulse width to the time length of each integration window, and The phase difference between the change curves of two adjacent difference values ​​in the difference values. Inputting it into MATLAB software will generate the output. This yields a change curve for each difference value over a time period. For example, when... When the ratio of the laser pulse width to the time length of each integration window is 5, six difference values ​​will be generated as curves of change in a single time period. Each time period consists of eight integration windows, and each integration window is a sub-period of a time period.

[0022] S2. Perform linear normalization on the curves of each difference value over a time period to obtain the normalized values. Several change curves, with preset horizontal axis intervals, respectively at... Collected from the normalized change curve. Each ordinate value will be collected from each normalized change curve. Using the y-coordinate values ​​as a basis vector, we obtain There are basis vectors.

[0023] It should be noted that the preset horizontal axis interval refers to the flight time interval, that is, the time length of the integration window.

[0024] S3. Collect data from L preset cosine-like curves at preset horizontal coordinate intervals. Each ordinate value will be collected from each change curve graph. Each ordinate value is used as a target vector, resulting in L target vectors.

[0025] For example, continue with Taking the ratio of the laser pulse width to the time length of each integration window as an example, where 5 is the ratio of the laser pulse width to the time length of each integration window, as an example, when... In this case, L=4, meaning four pre-defined cosine-like curves are needed. Similarly, the horizontal axis of each pre-defined cosine-like curve represents the ratio of flight time to the time length of each integration window, and the vertical axis represents the normalized number of trigger events. For example, Figure 3 The linear combinations 1, 2, 3, and 4 in the diagram are schematic diagrams of four preset cosine-like curves.

[0026] S4, according to L overdetermined equations are constructed using L basis vectors and L target vectors. The pseudo-inverse form of the least squares method is used to solve each overdetermined equation, and L sets of weight coefficients are obtained respectively.

[0027] For example, continuing with the above example, if we obtain 6 basis vectors... ~ and 4 target vectors ~ Then these 6 basis vectors ~ The columns are concatenated to form a coefficient matrix A, where... It is the first column of the coefficient matrix A. This is the second column of coefficient matrix A, and so on. The [column name] is the second column of coefficient matrix A. The group weight coefficient is taken as x, and the first group weight coefficient is taken as x. target vectors As vector b, to construct the first One overdetermined equation, namely , The value of is 1 to 4. Next, construct the... Augmented matrices corresponding to each overdetermined equation And determine the augmented matrix Whether the rank of the coefficient matrix A is equal to that of the matrix A, and if they are equal, indicates that... If a solution exists, then determine whether the coefficient matrix A is of full column rank. It should be noted that full column rank means the rank of a matrix is ​​equal to its number of columns; if A is of full column rank, then... If a unique exact solution exists, then the least squares pseudo-inverse form x = (A T A) 1 A T b calculates x, and the calculated x can be substituted into... The correctness of the solution is verified in the middle. If the verification passes, it means that the calculated x is correct. Thus, the first... Group weight coefficients. Based on this principle, the weight coefficients of the four groups can be calculated separately.

[0028] The rising edge determination unit 1303 performs simultaneous analysis on the modulation value sequence to obtain the structured data sequence where the rising edge of the echo occurs, and uses the storage address of the integration window corresponding to the maximum value in the structured data sequence where the rising edge of the echo occurs as the time index of the rising edge of the echo. This determination does not depend on the laser pulse width, but is based on the local maximum counting principle, thereby reducing the impact of pulse width on positioning accuracy. Specifically, for each modulation value in the modulation value sequence that is greater than 0 or less than 0, the rising edge determination unit 1303 determines the rising edge of the echo. The modulation value is determined by the first... The group weight coefficients are obtained by weighted summation of the elements in the eigenvalue sequence after the difference operation. Furthermore, as stated above, the first... The group weight coefficient corresponds to the first There are several preset cosine-like curves, and the x-axis of each preset cosine-like curve is the ratio of flight time to the length of the integration window. Each preset cosine-like curve changes periodically with different time periods. Each integration window constitutes a time period, and each integration window is a sub-period of a time period. Therefore, the rising edge determination unit 1303 determines the rising edge based on the first integration window. The sign of the modulation value, in the th modulation value From a single time period of a preset cosine-like curve, a sub-period range of flight time can be determined. Thus, L sub-period ranges can be obtained. Next, the intersection of these L sub-period ranges is determined, and this intersection is taken as a target sub-period g*. The structured data sequence numbered as the target sub-period g* can then be used as the structured data sequence containing the rising edge of the echo. For example, the rising edge determination unit 1303 includes a comparison circuit and a determination circuit. The comparison circuit is used to determine the rising edge based on the... The sign of the modulation value, in the th modulation value The group weight coefficient corresponding to the first The flight time is determined from the curve of a single time period of a preset cosine-like curve, resulting in L sub-period ranges. A decision circuit is used to determine the intersection of these L sub-period ranges, taking the intersection as the target sub-period g*. The structured data sequence numbered as the target sub-period g* is taken as the structured data sequence containing the rising edge of the echo, and the storage address of the integration window corresponding to the maximum value in the structured data sequence containing the rising edge of the echo is used as the rising edge time index. Continuing with the above... Taking a ratio of 5 between the laser pulse width and the time length of each integration window as an example, we can obtain four sub-period ranges. The intersection of these four sub-period ranges is the number of the structured data sequence containing the rising edge of the echo. For example, when these four sub-period ranges are (2, 6], (3, 7], (0, 4], and (1, 5], the intersection of these four sub-periods is 4. Therefore, the structured data sequence numbered 4 is taken as the structured data sequence containing the rising edge of the echo. Figure 2 If Obin3 is the structured data sequence where the rising edge of the echo is located, then the storage address of the integration window corresponding to the maximum value in Obin3 is used as the rising edge time index of the echo.

[0029] It should be noted that the echo rise time index is a numerical value. Therefore, in some embodiments, the time-of-flight calculation module 140 is used to directly use the echo rise time index as the indirect time of flight within the valid sub-interval. And based on the starting index of the valid sub-interval and the time length of each integration window. Calculate the start time of the sub-interval and the start time of the sub-interval and indirect flight time The sum of these values ​​represents the complete flight time, which is then converted into target depth based on the time-distance mapping. Specifically, the starting index of the effective sub-interval and the time length of each integration window are used. The product of these is the start time of the sub-interval. Sub-interval start time and indirect flight time The sum of these is the complete flight time. In this way, the complete flight time can be obtained quickly.

[0030] In some embodiments, such as Figure 1As shown, the time-of-flight calculation module 140 includes an indirect time-of-flight calculation unit 1401 and a depth calculation unit 1402. The indirect time-of-flight calculation unit 1401 calculates the indirect time of flight within the effective sub-interval based on the echo rise edge time index, the time length of each integration window, and the number of trigger events in each integration window within K consecutive integration windows, using the indirect time-of-flight calculation formula. The depth calculation unit 1402 is used to calculate the starting index of the effective sub-interval and the time length of each integration window. Calculate the start time of the sub-interval and the start time of the sub-interval and indirect flight time The sum of these values ​​is taken as the complete flight time. Based on the time-distance mapping relationship, the complete flight time is converted into target depth. In this way, a more accurate complete flight time can be obtained. It should be noted that how to use the time-distance mapping relationship to convert the complete flight time into target depth is an existing and well-known technical method, which will not be elaborated upon in this invention.

[0031] For example, indirect flight time The calculation formula is: ; in, Indicates indirect flight time. Indicates the rising edge time index of the echo. This indicates the duration of each integration window. This indicates the number of trigger events in the integration window corresponding to the rising edge time index of the echo. , and These represent memory addresses. , and The number of times the corresponding points window was triggered, and, , , and The corresponding integration windows are all contained within the valid subintervals.

[0032] For example, Figure 4 This is a schematic diagram illustrating the calculation principle of complete flight time. For example... Figure 5 As shown, the image, composed of multiple connected rectangles, represents the global histogram data for the entire measurement interval. This represents P consecutive integration windows and the number of trigger events within each of the P consecutive integration windows. The four rectangles within the red dashed box are used for calculation... The histogram data represents the calculation using the above formula. The number of trigger events for the four integration windows required at that time is shown. The fully red rectangular area represents the integration window corresponding to the echo rising edge index (i.e., the echo rising edge time index) and its trigger event count, such as... Figure 4 As shown, + That is the complete flight time.

[0033] This invention also provides a time-of-flight measurement method with weak coupling between laser pulse width and integration window, such as... Figure 5 As shown, the method includes: S101. Receive single-photon trigger event signals from SPAD pixels within each preset measurement cycle, and discretize and statistically analyze the single-photon trigger event signals until the end of the last preset measurement cycle to obtain global histogram data for the entire measurement interval. The histogram data consists of the number of trigger events in each of P consecutive integration windows, with each integration window corresponding to a storage address.

[0034] S102. Determine the peak position information based on the global histogram data, and determine the histogram data of the effective sub-intervals based on the peak position information to obtain local histogram data. The effective sub-intervals have a starting index, and the local histogram data is the number of trigger events of each integration window within K consecutive integration windows. K and P are both positive integers greater than 0, and K is less than P.

[0035] S103. Through differentiation, recombination and linear combination operations, the local histogram data is structured to obtain the echo rise time index.

[0036] S104. Based on the starting index of the effective sub-interval, the echo rising edge time index, and the indirect flight time calculation formula, generate the complete flight time and convert the complete flight time into the target depth.

[0037] By combining histogram statistics with structured indirect time-of-flight feature calculation, this invention maintains coverage comparable to direct time-of-flight methods in terms of overall detection range, thus breaking the limitation that traditional indirect time-of-flight methods are typically only applicable to short-range scenarios. Simultaneously, this invention constructs multiple features within effective sub-intervals and utilizes phase-type information for rising edge analysis, resulting in a significantly higher distance accuracy than direct time-of-flight methods that rely solely on histogram peak detection. Furthermore, by introducing differentiation-recombination and linear combination mechanisms, this invention weakens the dependence of indirect time-of-flight methods on strict matching of laser pulse width and integration window, allowing the laser pulse width to be flexibly set within a range of multiples of the integration window. This ensures good adaptability and robustness under different lighting conditions, reflection characteristics, and working distances, significantly improving the system's engineering usability. The high-precision wide dynamic range time-of-flight measurement method with decoupled laser pulse width and integration window provided by this invention can be applied to SPAD LiDAR, enabling SPAD LiDAR to build real-time 3D maps of the surrounding environment. This helps assist in autonomous driving and obstacle avoidance in vehicles, robot navigation, and the creation of realistic virtual scenes or augmented reality experiences.

[0038] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0039] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0040] In this specification, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple instances. While different embodiments may describe certain measures, this does not mean that these measures cannot be combined to produce a good effect.

[0041] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A time-of-flight measurement system with weak coupling between laser pulse width and integration window, characterized in that, include: The histogram statistics algorithm module is used to receive single-photon trigger event signals from SPAD pixels in each preset measurement cycle, and to discretize and statistically analyze the single-photon trigger event signals until the end of the last preset measurement cycle to obtain global histogram data for the entire measurement interval. The histogram data is the number of trigger events in each integration window within P consecutive integration windows, and each integration window corresponds to a storage address. The echo photon positioning module is used to determine peak position information based on the global histogram data, and to determine the histogram data of the effective sub-interval based on the peak position information, thereby obtaining local histogram data. The effective sub-interval has a starting index, and the local histogram data is the number of trigger events of each integration window within K consecutive integration windows, where K and P are both positive integers greater than 0, and K is less than P. The echo feature analysis module is used to perform structured processing on the local histogram data through differentiation, recombination and linear combination operations to obtain the echo rise time index. The time-of-flight calculation module is used to generate a complete time of flight based on the starting index of the effective sub-interval, the rising edge time index of the echo, and the indirect time-of-flight calculation formula, and to convert the complete time of flight into the target depth.

2. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 1, characterized in that, The histogram statistics algorithm module includes: The event receiving unit is used to receive single-photon trigger event signals from SPAD pixels in each preset measurement cycle, and convert each received single-photon trigger event signal into a timestamp information; The histogram accumulation unit has P consecutive integration windows, each corresponding to a storage address. Each preset measurement period covers the entire measurement interval, which is the time interval formed by the P consecutive integration windows. The histogram accumulation unit is used to convert each received timestamp information into a storage address within each preset measurement period, count the current number of trigger events in the integration window corresponding to the storage address, and then add one to the obtained statistical value to obtain the latest number of trigger events in the integration window corresponding to the storage address. This process continues until the end of the last preset measurement period, at which point the number of trigger events for each integration window is obtained, and the number of trigger events for each integration window within the P consecutive integration windows is used as the global histogram data for the entire measurement interval.

3. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 1, characterized in that, The echo photon positioning module includes: The peak detection unit is used to determine the maximum number of times from the number of trigger events corresponding to the P consecutive integration windows, and to use the storage address of the integration window corresponding to the maximum number of times as the peak position information. The interval extraction unit is used to take the integration window corresponding to the peak position information as the target integration window, expand the integration window before and after the target integration window along the time axis by a preset number of integration windows to obtain K consecutive integration windows, use the number of trigger events of each integration window in the K consecutive integration windows as histogram data of the effective sub-interval to obtain local histogram data, and use the storage address of the first integration window in the K consecutive integration windows as the starting index of the effective sub-interval.

4. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 1, characterized in that, The echo feature analysis module includes: The histogram differentiation and recombination unit is used to divide the number of K trigger events corresponding to the K consecutive integration windows into G subgroups according to a preset differentiation and recombination factor S. Each subgroup contains S number of trigger events, where the product of S and G equals K. The number of trigger events in the same sequence position in the G subgroups is recombined into a structured data sequence to obtain S structured data sequences. The elements in each structured data sequence are summed to obtain S feature values ​​corresponding to the S structured data sequences. The difference and feature combination unit is used to sequentially perform difference operations on the feature value sequence composed of the S feature values, and then perform L sets of linear combination operations on the feature value sequence after the difference operations using L sets of weight coefficients to obtain a modulation value sequence containing L modulation values ​​that vary with flight time, where L is... S and L are both positive integers greater than 1; The rising edge determination unit is used to perform simultaneous analysis on the modulation value sequence to obtain the structured data sequence in which the rising edge of the echo is located, and to use the storage address of the integration window corresponding to the maximum value in the structured data sequence in which the rising edge of the echo is located as the rising edge time index.

5. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 4, characterized in that, The difference and feature combination unit is specifically used to perform a difference operation on the feature value sequence composed of the S feature values ​​to obtain a sequence containing... The difference sequence of L difference values ​​is weighted and summed using each of the L sets of weighting coefficients, resulting in L summed values. Each set of weighting coefficients contains values ​​related to the difference sequence. Each difference value corresponds to one-to-one with There are L weighting coefficients, and the L summed values ​​are L modulation values ​​that vary with flight time. These L modulation values ​​constitute a modulation value sequence, where each modulation value is greater than 0 or less than 0. The modulation value is determined by the first... The group weight coefficients are obtained by weighted summation of the elements in the eigenvalue sequence after the difference operation. .

6. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 5, characterized in that, No. The group weight coefficient corresponds to the first There are several preset cosine-like curves, and the x-axis of each preset cosine-like curve is the ratio of flight time to the length of the integration window. Each preset cosine-like curve changes periodically with different time periods. A time period consists of several integration windows, and each integration window is a sub-period of a time period. It is a positive integer, and The value of is 1 to L; The rising edge determination unit is specifically used to determine the rising edge based on the first... The sign of the modulation value, in the th modulation value The group weight coefficient corresponding to the first The flight time is determined from the curve of a single time period of a pre-defined cosine-like curve, resulting in L sub-period ranges. Then, the intersection of the L sub-period ranges is determined, and the intersection is taken as the target sub-period g*. The structured data sequence numbered as the target sub-period g* is taken as the structured data sequence where the echo rise edge is located, and the storage address of the integration window corresponding to the maximum value in the structured data sequence where the echo rise edge is located is taken as the echo rise edge time index.

7. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 1, characterized in that, The time-of-flight calculation module includes: The indirect flight time calculation unit is used to calculate the indirect flight time within the effective sub-interval based on the echo rise edge time index, the time length of each integration window, and the number of trigger events in each integration window within the K consecutive integration windows, and using the indirect flight time calculation formula. The depth calculation unit is used to calculate the start time of the sub-interval based on the starting index of the effective sub-interval and the time length of each integration window, and to use the sum of the start time of the sub-interval and the indirect flight time as the complete flight time, and to convert the complete flight time into the target depth according to the mapping relationship between time and distance.

8. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 7, characterized in that, The formula for calculating the indirect flight time is as follows: ； in, Indicates the indirect flight time, This indicates the rising edge time index of the echo. This indicates the duration of each integration window. This indicates the number of trigger events in the integration window corresponding to the echo rise edge time index. , and These represent memory addresses. , and The number of times the corresponding points window was triggered, and, , , and The corresponding integration windows are all contained within the effective sub-intervals.

9. The time-of-flight measurement system with weak coupling between laser pulse width and integration window according to claim 4, characterized in that, The lower limit of the laser pulse width range is the time length of 2 integration windows, and the upper limit is the time length of S-1 integration windows.

10. A method for measuring time-of-flight with weak coupling between laser pulse width and integration window, characterized in that, include: In each preset measurement cycle, a single-photon trigger event signal from the SPAD pixel is received, and the single-photon trigger event signal is discretized and statistically analyzed until the last preset measurement cycle ends to obtain the global histogram data of the entire measurement interval. The histogram data is the number of trigger events in each integration window within P consecutive integration windows, and each integration window corresponds to a storage address. Based on the global histogram data, peak position information is determined, and based on the peak position information, histogram data of effective sub-intervals is determined to obtain local histogram data. The effective sub-intervals have starting indices, and the local histogram data is the number of trigger events of each integration window within K consecutive integration windows. K and P are both positive integers greater than 0, and K is less than P. The local histogram data is structured through differentiation, recombination, and linear combination operations to obtain the echo rise time index. Based on the starting index of the effective sub-interval, the rising edge time index of the echo, and the indirect time-of-flight calculation formula, the complete time of flight is generated and converted into the target depth.

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