Flight time measurement method and device, storage medium and laser radar

Abstract

The embodiment of the invention discloses a flight time measurement method and device, a storage medium and a laser radar, and relates to the field of measurement. According to the method, firstly, the laser radar is set to be in a calibration mode, and preparation is made for follow-up precise calibration; transmitting a signal to a calibration object with a known distance at a 0-phase gear, obtaining a reflected signal intensity value, and fitting a first flight time response model coefficient by using multiple groups of data points; and repeating the operation at the 90-phase gear, and fitting a second model coefficient. And calculating factors such as theta, phi and R by using the fitting coefficient. And then the laser radar is switched to a measurement mode, and the intensity values of the to-be-measured object at the 0-degree phase and the 90-degree phase are obtained. And calculating a cosine value and a sine value according to the intensity value and the calculated factor. Finally, flight time is calculated according to the sine value and the cosine value, and high-precision flight time calculation is achieved through the steps of model establishment, factor calculation and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of measurement, in particular to a time-of-flight measurement method and device, a storage medium and a laser radar. BACKGROUND

[0002] i-TOF (indirect time-of-flight) laser radars have been widely used in many fields such as autonomous driving, robot navigation, industrial detection, etc. due to their significant advantages of low cost, compact design and high spatial resolution. The working principle is to calculate the time-of-flight of an object by emitting a modulated laser signal and measuring the phase difference between the reflected signal and the emitted signal, and then to obtain the distance information of the object.

[0003] However, in actual operation, the measurement accuracy and stability of the i-TOF system are severely restricted by various error factors. In terms of systematic errors, there are problems such as offset, wiggling error and fixed pattern noise (FPN). Among them, the complex coupling phenomenon between wiggling error and FPN is particularly prominent, which leads to time-of-flight response non-uniformity (TFRNU) and greatly affects the accuracy of the measurement results. In terms of random errors, readout noise and photon noise also interfere with the measurement results.

[0004] Currently, in order to solve the problem of wiggling error, existing technologies mainly start from two directions of hardware optimization and software compensation. In terms of hardware optimization, methods such as waveform modulation and duty cycle adjustment are adopted. For example, by adjusting the shape and duty cycle of the laser emission waveform, it is attempted to improve the stability of the laser signal and thus reduce the generation of wiggling error. In terms of software compensation, look-up table and B-spline interpolation techniques are widely used. The look-up table stores error compensation values under different conditions in advance, and queries and compensates in actual measurement; the B-spline interpolation uses mathematical methods to fit and correct the measurement data.

[0005] For the FPN problem, delay line self-compensation circuit and deep learning algorithm are common improvement means. The delay line self-compensation circuit adjusts and compensates the signal in time by introducing a delay line structure to reduce the influence of FPN. The deep learning algorithm learns the characteristics and rules of FPN by using a large amount of training data, and then intelligently compensates in the measurement process.

[0006] However, these existing methods have many problems in terms of accuracy, complexity and applicability.

[0007] In terms of accuracy, the existing methods have limited effect, which can only reduce the root mean square error (RMSE) of system error from tens of millimeters to 5-10 millimeters, which is far from the theoretical sub-millimeter accuracy limit of i-TOF system. This means that in practical applications, there is still a large error in the measurement results, which cannot meet the demand of high-precision measurement.

[0008] In terms of complex coupling, the source of FPN is extremely complex, involving multiple hardware components and signal processing links of the lidar. Moreover, the multi-source coupling mechanism between FPN and wobble error has not been fully understood. Due to the lack of understanding of this coupling mechanism, existing algorithms are difficult to achieve comprehensive suppression of errors and cannot fundamentally solve the TFRNU problem.

[0009] In terms of high manufacturing cost, in order to improve the measurement accuracy, the existing solutions have strict requirements on the CMOS manufacturing process. For example, in order to achieve more accurate signal modulation and processing, a higher precision manufacturing process is required, which undoubtedly increases the manufacturing cost and process complexity of the chip. At the same time, complex hardware optimization and software compensation methods also increase the overall cost and development difficulty of the system, limiting the application of i-TOF lidar in some cost-sensitive fields.

[0010] Therefore, there is an urgent need for a new technical solution to effectively solve the error problem in i-TOF lidar, improve measurement accuracy, reduce manufacturing cost, and promote the widespread application of i-TOF lidar in more fields. SUMMARY

[0011] Embodiments of the present application provide a time-of-flight measurement method, device, storage medium and lidar, which can solve the problems of high cost and large error in measuring time-of-flight of the existing technology. The technical solution is as follows: In a first aspect, the embodiments of the present application provide a time-of-flight measurement method, which comprises: setting the lidar to a calibration mode; under the 0 phase gear, emitting a measurement laser signal to a known distance calibration object, and acquiring the intensity value I of the corresponding reflected laser signal AC-C , fitting the coefficients m FT and m AC-C of the first time-of-flight response model using multiple sets of data points (t AC1 , I AC2 ; the first time-of-flight response model is: I AC-C =m AC1 *cos(2π*t FT / T)+m AC2 *cos(2π*t FT / T), T represents the period of the measured laser signal, the measured laser signal is a sinusoidal amplitude modulated laser signal, t FT Indicates the flight time of the calibration object; At the 90° phase position, a measuring laser signal is emitted to a calibration object at a known distance, and the intensity value I of the reflected laser signal is obtained. BD-C , according to the multiple sets of data points obtained during the calibration process (t FT , I BD-C ) Fit the coefficient m of the second time-of-flight response model BD1 and m BD2 The second flight time response model is represented by I BD-C =m BD1 *cos(2π*t FT / T)+m BD2 *cos(2π*t FT / T); Calculate the factors: θ, φ and R using the fitted coefficients; θ=arctan[(m AC1 ^2+m AC2 ^2)^1 / 2] / [(m BD1 ^2+m BD2 ^2)^1 / 2]; R=(m AC1 ^2+m AC2 ^2+m BD1 ^2+m BD2 ^2)^1 / 2; φ=arctan(m AC1 / m AC2 )=arctan(m BD1 / m BD2 ); Switch the laser radar to measurement mode and obtain the intensity value I of the object to be measured at the 0 phase position. AC and the intensity value I at 90 degrees phase BD ; According to the above intensity value I AC , intensity value I BD , θ, φ and R calculate the cosine and sine values ​​cos(2π*t FT / T) and sin(2π*t FT / T): ; Calculate the flight time t based on the calculated sine and cosine values FT , .

[0012] In a second aspect, an embodiment of the present application provides a device for measuring time of flight, the device comprising: A setting unit, used to set the laser radar to a calibration mode; The fitting unit is used to transmit a measuring laser signal to a calibration object of known distance through the transmitter at the 0 phase position, and obtain the intensity value I of the corresponding reflected laser signal. AC-C , using multiple sets of data points (t FT , I AC-C ) Fit the coefficient m of the first time-of-flight response model AC1 and m AC2 ; The first flight time response model is: I AC-C =m AC1 *cos(2π*t FT / T)+m AC2 *cos(2π*t FT / T), T represents the period of the measured laser signal, the measured laser signal is a sinusoidal amplitude modulated laser signal, t FT Indicates the flight time of the calibration object; The fitting unit is further configured to transmit a measuring laser signal to a calibration object at a known distance through a transmitter at a 90° phase position, and obtain an intensity value I of the reflected laser signal. BD-C , according to the multiple sets of data points obtained during the calibration process (t FT , I BD-C ) Fit the coefficient m of the second time-of-flight response model BD1 and m BD2 The second flight time response model is represented by I BD-C =m BD1 *cos(2π*t FT / T)+m BD2 *cos(2π*t FT / T); A calculation unit for calculating factors: θ, φ and R using the fitted coefficients; θ=arctan[(m AC1 ^2+m AC2 ^2)^1 / 2] / [(m BD1 ^2+m BD2 ^2)^1 / 2]; R=(m AC1 ^2+m AC2 ^2+m BD1 ^2+m BD2 ^2)^1 / 2; φ=arctan(m AC1 / m AC2 )=arctan(m BD1 / m BD2 ); A measurement unit is configured to switch the laser radar to a measurement mode, and acquire intensity values I of the object to be measured at 0 phase position and 90 degree phase position. AC and 90 degree phase position. BD ; The calculation unit is further configured to calculate cosine values and sine values cos(2π*t AC , I BD , θ, φ and R respectively according to the intensity values I FT / T) and sin(2π*t FT / T) based on the intensity values I ; The calculation unit is further configured to calculate the time of flight t FT , .

[0013] In a third aspect, the embodiments of the present application provide a computer storage medium, which stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and performing the method steps described above.

[0014] In a fourth aspect, the embodiments of the present application provide a laser radar, which can include a processor and a memory, wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and performing the method steps described above.

[0015] The technical solutions provided by some embodiments of the present application have at least the following beneficial effects: By establishing a time of flight response model, quantifying the amplitude deviation and phase delay caused by FPN (Fixed Pattern Noise) and wobble error, and correcting by using a weighted normalization technique, high-precision time of flight calculation is realized. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0017] Figure 1 is a system architecture diagram provided by the embodiments of the present application; Figure 2 is a flowchart of a time of flight measurement method provided by the embodiments of the present application; Figure 3 is a structural diagram of a time of flight measurement device provided by the present application; Figure 4is a structural schematic diagram of a computer program provided by the present application. Figure 5 is a structural schematic diagram of a laser radar provided by the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the drawings.

[0019] Figure 1 An exemplary system architecture of a time-of-flight measurement method or a time-of-flight measurement device that can be applied to the present application is shown.

[0020] As shown in Figure 1 , the system architecture can include an object to be measured 101 and a laser radar 102. The laser radar 102 includes a controller, a driving chip, a transmitter and a receiver. The controller controls the driving voltage and driving current of the driving chip, the transmitter is used to transmit a sinusoidal probe signal, and the receiver is used to receive a reflection signal of the object to be measured and measure the intensity value of the reflected laser signal. The receiver is generally a matrix provided with a plurality of pixel units. The phase difference between the sinusoidal probe signal and the reflection signal is Δφ. The controller calculates the indirect time-of-flight according to the phase difference, and thus calculates the distance between the object to be measured.

[0021] The time-of-flight measurement method provided by the embodiments of the present application will be described in detail below. Figure 2 , the time-of-flight measurement device in the embodiments of the present application can be a laser radar as shown in Figure 1 .

[0022] Please refer to Figure 2 , a flowchart of a time-of-flight measurement method provided by the embodiments of the present application is shown. As shown in Figure 2 , the method provided by the embodiments of the present application can include the following steps: S201, set the laser radar to a calibration mode.

[0023] Among them, the laser radar usually has different working modes, and through specific control instructions or hardware settings, the laser radar is switched from the normal measurement mode to the calibration mode. In the calibration mode, some parameter settings and data processing methods of the laser radar will be different from those in the normal measurement mode, so as to perform subsequent calibration operations. For example, the emission power, receiving sensitivity and other parameters of the laser can be adjusted to make them more suitable for the calibration process.

[0024] For example, the operator can select the "calibration mode" option through the software interface matched with the lidar, and the software will send the corresponding control signal to the lidar. After receiving the signal, the internal control circuit of the lidar will adjust the relevant parameters and enter the calibration mode.

[0025] S202, under the 0 phase gear, a measuring laser signal is emitted to a known distance calibration object, and a corresponding reflected laser signal intensity value I is obtained AC-C , a plurality of sets of data points (t FT , I AC-C ) are used to fit the coefficients m AC1 and m AC2 of the first time-of-flight response model.

[0026] Wherein, under the 0 phase gear, the lidar emits a sinusoidal measuring laser signal according to the set measuring laser signal period T, and the 0 degree phase represents that the phase difference between the emitted measuring laser signal and the received reflected signal is 0 degrees. When the measuring laser signal reaches the known distance calibration object, it will be reflected, and the receiving module of the lidar will receive the reflected signal and measure the intensity value I of the reflected laser signal AC-C . At the same time, according to the known distance of the calibration object, the corresponding time of flight t FT can be calculated. By changing the position of the calibration object (i.e. changing the time of flight t FT ), a plurality of sets of data points (t FT , I AC-C ) are obtained. Then, using a mathematical fitting method (such as the least squares method), these data points are substituted into the first time-of-flight response model I AC-C =m AC1 *cos(2π*t FT / T)+m AC2 *cos(2π*t FT / T), and the coefficients m AC1 and m AC2 are solved.

[0027] For example, assuming that the measuring laser signal period T=10ns, and the known distance of the calibration object is 1m, according to the speed of light c=3×10 8 m / s, the time of flight t FT =2×1 / c≈6.67ns can be calculated. At this distance, the lidar emits a measuring laser signal and obtains the intensity value I AC-C of the reflected signal. Then change the distance of the calibration object to 2m, 3m, etc. and repeat the above operation to obtain a plurality of sets of data points (t FT , I AC-C ). The least squares method is used to fit these data points to obtain m AC1 and m AC2the value of the first flight time response model and the second flight time response model.

[0028] In some possible embodiments of the present application, the calibration object is a reflective plate arranged outside the lidar, and the measurement is performed by measuring the laser signal after multiple reflections by the mirror to the calibration object.

[0029] In some possible embodiments of the present application, the calibration object is a reflective plate arranged outside the lidar, and the measurement is performed by measuring the laser signal after multiple reflections by the mirror to the calibration object.

[0030] At the same time, in order to adapt to different calibration requirements, the calibration object can have certain adjustment mechanism. For example, it can be moved within a limited range through a fine adjustment mechanism to simulate different flight time conditions. But this adjustment is within a known and controllable range, ensuring that the position after each adjustment can be accurately measured and recorded.

[0031] In the calibration process, the lidar emits measurement laser signals to this internal calibration object at 0 phase and 90 phase. Since the calibration object is inside the radar, the signal propagation path is relatively stable, reducing the influence of external environmental factors (such as air disturbance, interference of other objects, etc.) on the signal. This makes the obtained reflection signal intensity value more accurate and reliable, which is conducive to the accurate fitting of the first flight time response model and the second flight time response model coefficients.

[0032] In some possible embodiments of the present application, before the lidar performs the fitting work of the first flight time response model and the second flight time response model, data cleaning operation is carried out on the collected multiple groups of data points (t FT , I AC-C ) and multiple groups of data points (t FT , I BD-C ), which is a key step to ensure the quality of model fitting.

[0033] The primary task of data cleaning is to identify and process abnormal data. In the actual measurement process, due to the existence of various interference factors, some data points that do not conform to the normal law may be collected. For example, when measuring the reflection signal intensity values I AC-C and I BD-C , they may be affected by sudden high-intensity electromagnetic interference from the outside world, resulting in abnormal high or low values of the received signal intensity. For the flight time t FT and t FTIt is also possible that the measurement value deviates from the true value due to temporary failure inside the lidar or temporary obstruction of external objects.

[0034] To identify these abnormal data, a statistical analysis method can be used. The mean and standard deviation of the data points are calculated, and a reasonable range is set, usually a range centered on the mean and several times the standard deviation as the boundary. If a data point is outside this range, it is considered abnormal data. For example, for a set of (t FT , I AC-C ) data points, the mean and standard deviation of I AC-C are calculated, and when the difference between a certain I AC-C value and the mean exceeds three times the standard deviation, the data point is marked as abnormal.

[0035] In addition to the identification of abnormal data, data cleaning also includes consistency checking of data. In the process of multiple measurements, since the measurement conditions should be in a relatively stable state, the data should have certain continuity and consistency between them. If it is found that some data points are obviously contradictory in change trend with other data points in the same group, further analysis and processing of these data are also needed. For example, when continuously measuring different distance calibration objects, the time of flight t FT should gradually increase, and the reflected signal intensity value I AC-C should gradually decrease. If a data point shows the opposite trend, the accuracy of the data point needs to be checked.

[0036] For the identified abnormal data and data points with consistency problems, they can be selected for rejection or correction. If the abnormal data is caused by temporary interference and the number is small, it can be directly rejected, and the remaining normal data is used for model fitting. For some data points that may have slight deviations, they can be reasonably corrected according to the rules of the surrounding data points.

[0037] S203, under the 90 phase gear, emit a measurement laser signal to a known distance calibration object, and acquire the intensity value I BD-C of the reflected laser signal, and according to the multiple sets of data points (t FT , I BD-C ) obtained in the calibration process, fit the coefficients m BD1 and m BD2 of the second time of flight response model.

[0038] Among them, the lidar is switched to the 90 phase gear, at which time the phase difference between the measurement laser signal and the received reflected signal is 90 degrees. Similarly, a measurement laser signal is emitted to a known distance calibration object, and the intensity value I BD-C of the reflected signal is measured. According to the distance of the calibration object, the corresponding time of flight tFT By changing the position of the calibration object multiple times, multiple sets of (t FT , I BD-C ) data points are obtained. These data points are substituted into the second time-of-flight response model I BD-C = m BD1 *cos(2π*t FT / T) + m BD2 *cos(2π*t FT / T), and the coefficients m BD1 and m BD2 are solved using a mathematical fitting method.

[0039] For example, at 90 phase gear, the measurement laser signal period T = 10 ns is kept unchanged. The calibration object is placed at 1.5 m, and the time of flight t FT = 2*1.5 / c = 10 ns is calculated, and the reflected signal intensity value I BD-C at this time is obtained. The calibration object is changed to different distances, such as 2.5 m, 3.5 m, etc., and multiple sets of (t FT , I BD-C ) data points are obtained, and the values of m BD1 and m BD2 are fitted.

[0040] In some possible embodiments of the present application, multiple sets of data points are obtained using calibration objects at multiple different distances.

[0041] Specifically, during the calibration process, the laser radar measures at calibration objects at multiple different distances. For the first time-of-flight response model, at 0 phase gear, the controller controls the laser radar to perform four different signal transmissions and receptions according to a certain time interval and step. The reflected signal intensity values obtained by each measurement are assigned different weights according to their measurement accuracy, environmental interference factors, etc.

[0042] For example, under certain measurement conditions, since the environmental light interference is small and the signal reception quality is high, the data obtained at this time is assigned a larger weight; conversely, the data obtained in the case of greater interference is assigned a relatively smaller weight. In this way, the measurement data can be more reasonably utilized, and the influence of data with greater errors on model fitting can be reduced.

[0043] For the second time-of-flight response model, at 90 phase gear, the controller accurately controls the change of the calibration object and the measurement process, obtains the reflected signal intensity values at different instances, and assigns corresponding weights according to the actual situation.

[0044] The coupling error of wobble and FPN (fixed pattern noise) is an important factor affecting the fitting accuracy of the model. The wobble may be caused by mechanical vibration of the laser radar itself, unstable laser emission and other factors, while the FPN is the noise generated due to the inherent characteristics of the receiver and other hardware. The present application can effectively separate the influence of wobble and FPN on the measurement results through multiple measurements and weighted processing. Because the performance of wobble and FPN is different under different conditions, through multiple distance measurements and weighted analysis, their coupling effect can be identified and eliminated, thereby improving the accuracy of model fitting.

[0045] S204, calculating factors: θ, φ and R using the fitted coefficients.

[0046] wherein θ = arctan[(m AC1 ^2+m AC2 ^2)^1 / 2] / [(m BD1 ^2+m BD2 ^2)^1 / 2]; R = (m AC1 ^2+m AC2 ^2+m BD1 ^2+m BD2 ^2)^1 / 2; φ = arctan(m AC1 / m AC2 ) = arctan(m BD1 / m BD2 ).

[0047] According to the coefficients m AC1 , m AC2 , m BD1 and m BD2 obtained by the previous fitting, θ, φ and R are calculated according to the given formula. The calculation of θ is by calculating the square root of the combination of the coefficients at 0 phase position and 90 phase position respectively, and then taking their arctangent values. The calculation of R is to calculate the square root of the sum of the squares of all coefficients. The calculation of φ is to calculate the arctangent values of the ratios of m AC1 to m AC2 , m BD1 to m BD2 respectively at 0 phase position and 90 phase position. Theoretically, the two arctangent values are equal.

[0048] S205, switching the laser radar to measurement mode to obtain the intensity value I AC at 0 phase position and the intensity value I BD at 90 degree phase of the object to be measured.

[0049] The laser radar is switched from calibration mode to measurement mode through control instructions. In measurement mode, the laser radar transmits measurement laser signals to the object to be measured at 0 phase position and 90 phase position, receives the reflected signals and measures the corresponding intensity values ​​I respectively. AC and I BD For example, a physical button is provided on the laser radar to switch between calibration mode and measurement mode. After the calibration is successfully completed, the user is prompted. The prompt can be a voice prompt or a text prompt on the display.

[0050] It should be noted that the lidar can automatically enter the calibration mode after it is turned on, or it can enter the measurement mode according to the user's selection. If it enters the measurement mode directly, the lidar uses the model parameters stored last time for measurement.

[0051] For example: the operator selects "measurement mode" through the software interface. After the laser radar switches to this mode, it first transmits the measurement laser signal at the 0 phase position, receives and measures the reflected signal intensity to obtain I AC Then switch to the 90-degree phase position and repeat the above operation to obtain I BD .

[0052] S206, according to the above strength value I AC , intensity value I BD , θ, φ and R calculate the cosine and sine values ​​cos(2π*t FT / T) and sin(2π*t FT / T).

[0053] The calculation is performed using specific mathematical formulas using the acquired IAC, IBD, and the previously calculated θ, φ, and R. These formulas are derived based on the previously established model and calibration parameters, and are intended to extract the cosine and sine values ​​related to the flight time from the measured intensity values: .

[0054] S207, calculate the flight time t according to the calculated sine value and cosine value FT .

[0055] Among them, according to the relationship between trigonometric functions, it is known that cos(2π*t FT / T) and sin(2π*t FT / T) can be calculated by mathematical methods such as the inverse tangent function to obtain 2π*t FT / T value, and then calculate the flight time t FT : .

[0056] Further, the laser pulses emitted by the laser radar will be reflected after encountering the object to be measured, and the reflected laser is captured by the receiving module of the laser radar. The time of flight t FT is the time interval experienced by the laser from emission to reception.

[0057] Since the laser travels back and forth between the laser radar and the object to be measured, the actual propagation distance is twice the distance from the laser radar to the object to be measured. According to the basic formula that distance is equal to speed multiplied by time, let the distance from the laser radar to the object to be measured be D, then the formula D = c x t FT / 2 can be obtained.

[0058] The present application has the following advantages: By using multiple sets of data points to fit the first time-of-flight response model and the second time-of-flight response model at 0 phase position and 90 phase position, a mathematical model capable of describing the measurement characteristics of the laser radar is successfully established. The originally abstract FPN and swing error are concretized, and the amplitude deviation and phase delay caused by these errors can be quantified.

[0059] Using the fitted coefficients to calculate θ, φ and R, etc. to indirectly adjust and correct the measurement data can effectively compensate for errors in the measurement process, making the calculation result closer to the true value.

[0060] After a series of model establishment, factor calculation and weighted normalization technology correction, high-precision time-of-flight calculation is finally realized. Accurate time-of-flight calculation is the key to i-TOF laser radar to obtain accurate distance information, and this technical solution effectively solves the influence of FPN and swing error on measurement accuracy.

[0061] The following is an embodiment of the device of the present application, which can be used to execute the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0062] Please refer to Figure 3 , which shows the structure diagram of the time-of-flight measurement device provided by an exemplary embodiment of the present application, hereinafter referred to as device 3. The device 3 can be realized by software, hardware or a combination of the two to become all or part of the laser radar. The device 3 comprises: a setting unit 301, a fitting unit 302, a calculation unit 303 and a measurement unit 304.

[0063] The setting unit 301 is used to set the laser radar to calibration mode. The fitting unit 302 is used to emit a measurement laser signal to a known distance calibration object through the transmitter at 0 phase position, and acquire the intensity value I AC-C of the corresponding reflected laser signal, and use multiple sets of data points (tFT , I AC-C ) fitting the coefficients m AC1 and m AC2 of a first time-of-flight response model, the first time-of-flight response model being I AC-C =m AC1 *cos(2π*t FT / T)+m AC2 *cos(2π*t FT / T), T representing a period of the measurement laser signal, the measurement laser signal being a sinusoidal signal, t FT representing a time of flight of the calibration object; The fitting unit 302 is further configured to, in the 90 phase gear, emit a measurement laser signal to a calibration object with a known distance through the emitter, and acquire an intensity value I BD-C of the reflected laser signal, and fit the coefficients m FT and m BD-C of a second time-of-flight response model according to a plurality of data points (t BD1 , I BD2 ) acquired in the calibration process, the second time-of-flight response model being I BD-C =m BD1 *cos(2π*t FT / T)+m BD2 *cos(2π*t FT / T), t FT representing a time of flight of the calibration object; The calculation unit 303 is configured to calculate factors θ, φ and R by using the fitted coefficients; θ=arctan[(m AC1 ^2+m AC2 ^2)^1 / 2] / [(m BD1 ^2+m BD2 ^2)^1 / 2]; R=(m AC1 ^2+m AC2 ^2+m BD1 ^2+m BD2 ^2)^1 / 2; φ=arctan(m AC1 / m AC2 )=arctan(m BD1 / m BD2 ); The measurement unit 304 is configured to switch the laser radar to a measurement mode, and acquire an intensity value I AC of the object to be measured in the 0 phase gear and an intensity value I BD in the 90 degree phase; The calculation unit 303 is further configured to calculate the distance of the object to be measured according to the intensity values IAC , intensity value I BD , and R, respectively, calculate cosine and sine values cos(2π*t FT / T) and sin(2π*t FT / T): ; The calculation unit 303 is further configured to calculate a time of flight t FT , .

[0064] In one or more possible embodiments, the entity-based key switching calibrates a mode and a measurement mode.

[0065] In one or more possible embodiments, the calibration object is disposed inside the laser radar.

[0066] In one or more possible embodiments, a plurality of sets of data points are obtained according to calibration objects at a plurality of different distances.

[0067] In one or more possible embodiments, a distance D = c x t FT / 2 between the to-be-measured objects is calculated according to the calculated time of flight.

[0068] In one or more possible embodiments, data cleaning is performed on the plurality of sets of data points (t FT , I AC-C ) and the plurality of sets of data points (t FT , I BD-C ) before model fitting.

[0069] It should be noted that the device 3 provided in the above embodiments is only used as an example to divide the above functional modules when performing the time-of-flight measurement method. In actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above functions. In addition, the time-of-flight measurement device and the time-of-flight measurement method provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be repeated here.

[0070] The serial numbers of the above embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0071] Referring to Figure 4 , the computer storage medium provided in the embodiments of the present application can be a magnetic disk, an optical disk, a magnetic tape, or a U disk, etc. The computer storage medium can store a plurality of instructions (i.e., a computer program), and the instructions are suitable for being loaded and executed by a processor to perform the method steps of the embodiments shown in the above Figure 2 The specific execution process can be seen in the above method embodiments.Figure 1 The specific description of the embodiments shown will not be repeated here.

[0072] The application also provides a computer program product, which stores at least one instruction loaded and executed by the processor to realize the time-of-flight measurement method according to various embodiments.

[0073] Please refer to Figure 5 A structural schematic diagram of a laser radar is provided for the embodiments of the application. As shown in Figure 5 The laser radar 500 can include at least one processor 501, at least one receiver 504, a transmitter 503, a memory 505, and at least one communication bus 502.

[0074] The communication bus 502 is used to realize the connection and communication between the components.

[0075] The transmitter 503 is used to transmit a sinusoidal signal, which can be an infrared signal, a laser signal, or an ultrasonic signal.

[0076] The receiver 504 is used to receive a reflected signal based on the reflection of the transmitted sinusoidal signal, and the transmitted signal and the reflected signal have a certain phase difference.

[0077] The processor 501 can include one or more processing cores. The processor 501 connects various parts in the terminal 500 through various interfaces and lines, executes various functions and processes data of the terminal 500 by running or executing instructions, programs, code sets or instruction sets stored in the memory 505, and calling data stored in the memory 505. Optionally, the processor 501 can be realized in at least one of the hardware forms of a digital signal processing (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA).

[0078] The memory 505 can include a random access memory (RAM) and a read-only memory (ROM). Optionally, the memory 505 includes a non-transitory computer-readable storage medium. The memory 505 can be used to store instructions, programs, codes, code sets, or instruction sets. The memory 505 can include a program storage area and a data storage area, where the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above various method embodiments, etc., and the data storage area can store data involved in the above various method embodiments, etc. The memory 505 can also be at least one storage device located away from the processor 501. As shown in Figure 5 The memory 505 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an application program.

[0079] In the laser radar 500 as shown in Figure 5 The processor 501 can be used to call the application program stored in the memory 505 and specifically execute the method as shown in Figure 2 The specific process can refer to Figure 2 which will not be described here.

[0080] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The program can be stored in a computer readable storage medium and can include the processes of the above-mentioned method embodiments when executed. The storage medium can be a magnetic disc, an optical disc, a read-only memory, or a random access memory, etc.

[0081] The above disclosure is only the preferred embodiments of the present application, and of course cannot limit the scope of the rights of the present application, so the equivalent changes made according to the claims of the present application still fall within the scope of the present application.

Claims

1. A method for measuring time of flight, characterized in that: include: Set the lidar to calibration mode; At the 0 phase position, a measuring laser signal is emitted to a calibration object at a known distance, and the intensity value I of the corresponding reflected laser signal is obtained. AC-C , using multiple sets of data points (t FT , I AC-C ) Fit the coefficient m of the first time-of-flight response model AC1 and m AC2 ; The first flight time response model is: I AC-C =m AC1 *cos(2π*t FT T)+m AC2 *cos(2π*t FT / T), T represents the period of the measured laser signal, the measured laser signal is an amplitude sinusoidally modulated laser signal, t FT The flight time of the light to calibrate the object is obtained by measuring the distance d of the object and the speed of light c. FT =2*d / c; At the 90° phase position, a measuring laser signal is emitted to a calibration object at a known distance, and the intensity value I of the reflected laser signal is obtained. BD-C , according to the multiple sets of data points obtained during the calibration process (t FT , I BD-C ) Fit the coefficient m of the second time-of-flight response model BD1 and m BD2 The second flight time response model is represented by I BD-C =m BD1 *cos(2π*t FT / T)+m BD2 *cos(2π*t FT / T) ; Calculate the factors: θ, φ and R using the fitted coefficients; θ=arctan[(m AC1 ^2+m AC2 ^2)^1 / 2] / [(m BD1 ^2+m BD2 ^2)^1 / 2]; R=(m AC1 ^2+m AC2 ^2+m BD1 ^2+m BD2 ^2)^1 / 2; φ=arctan(m AC1 / m AC2 )=arctan(m BD1 / m BD2 ); Switch the laser radar to measurement mode and obtain the intensity value I of the object to be measured at the 0 phase position. AC and the intensity value I at 90 degrees phase BD ; According to the above intensity value I AC , intensity value I BD , θ, φ and R calculate the cosine and sine values ​​cos(2π*t FT / T) and sin(2π*t FT / T): ; Calculate the flight time t based on the calculated sine and cosine values FT , .

2. The method according to claim 1, characterized in that Switch between calibration mode and measurement mode based on physical buttons.

3. The method according to claim 1, characterized in that The calibration object is a reflector arranged outside the laser radar.

4. The method according to claim 1, wherein Multiple sets of data points are obtained based on multiple calibration objects at different distances.

5. The method according to claim 1, wherein Calculate the distance d = c × t from the object to be measured based on the calculated flight time FT / 2.

6. The method according to claim 1, characterized in that Before model fitting, multiple sets of data points (t FT , I AC-C ) and multiple sets of data points (t FT , I BD-C ) to clean the data.

7. A flight time measuring device, characterized in that: include: A setting unit, used to set the laser radar to a calibration mode; The fitting unit is used to transmit a measuring laser signal to a calibration object of known distance through the transmitter at the 0 phase position, and obtain the intensity value I of the corresponding reflected laser signal. AC-C , using multiple sets of data points (t FT , I AC-C ) Fit the coefficient m of the first time-of-flight response model AC1 and m AC2 ; The first flight time response model is: I AC-C =m AC1 *cos(2π*t FT / T)+m AC2 *cos(2π*t FT / T), T represents the period of the measured laser signal, the measured laser signal is a sinusoidal signal, t FT Indicates the flight time of the calibration object; The fitting unit is further configured to transmit a measuring laser signal to a calibration object at a known distance through a transmitter at a 90° phase position, and obtain an intensity value I of the reflected laser signal. BD-C , according to the multiple sets of data points obtained during the calibration process (t FT , I BD-C ) Fit the coefficient m of the second time-of-flight response model BD1 and m BD2 The second flight time response model is represented by I BD-C =m BD1 *cos(2π*t FT / T)+m BD2 *cos(2π*t FT / T), t FT The flight time of light to and from the calibration object is obtained by measuring the distance d to the object and the speed of light c. FT =2*d / c; A calculation unit for calculating factors: θ, φ and R using the fitted coefficients; θ=arctan[(m AC1 ^2+m AC2 ^2)^1 / 2] / [(m BD1 ^2+m BD2 ^2)^1 / 2]; R=(m AC1 ^2+m AC2 ^2+m BD1 ^2+m BD2 ^2)^1 / 2; φ=arctan(m AC1 / m AC2 )=arctan(m BD1 / m BD2 ); The measuring unit is used to switch the laser radar to the measuring mode and obtain the intensity value I of the object to be measured at the 0 phase position. AC and the intensity value I at 90 degrees phase BD ; The calculation unit is further configured to calculate the intensity value I AC , intensity value I BD , θ, φ and R calculate the cosine and sine values ​​cos(2π*t FT / T) and sin(2π*t FT / T): ; The calculation unit is further used to calculate the flight time t according to the calculated sine value and cosine value FT , .

8. A computer storage medium, characterized in that The computer storage medium stores a plurality of instructions, which are suitable for being loaded by a processor and executing the method steps according to any one of claims 1 to 6.

9. A laser radar, characterized in that: include: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method steps according to any one of claims 1 to 6.

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