CN108732553B - Laser radar waveform time identification method and online ranging system - Google Patents
Laser radar waveform time identification method and online ranging system Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/483—Details of pulse systems
- G01S7/486—Receivers
- G01S7/487—Extracting wanted echo signals, e.g. pulse detection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/42—Simultaneous measurement of distance and other co-ordinates
Abstract
The invention discloses a laser radar waveform time identification method and an online ranging system, which realize online processing and real-time ranging of laser radar signal waveforms; the laser radar high-speed acquisition and processing unit acquires pulse signals output by the detection and receiving unit, and a programmable processor of the high-speed acquisition and processing unit determines a target function and a fitting parameter vector thereof through waveform characteristics, determines a signal effective range and realizes waveform cutting; calculating an initial fitting objective function on line based on the cutting waveform, calculating the difference between the initial fitting objective function and the collected signal in real time to determine a residual vector, and calculating the residual vector partial derivatives in parallel to determine a Jacobian matrix; determining the optimal condition of a residual vector based on a Jacobian matrix, and calculating a final fitting objective function on line; determining pulse time based on the online fitting parameter vector, calculating a target distance, combining ranging data and waveform data, and uploading to an upper computer for display and storage; the method can realize online waveform parameter vector extraction, distance calculation and point cloud generation.
Description
Technical Field
The invention relates to the field of laser radar measurement, in particular to a laser radar waveform time identification method and an online ranging system.
Background
The laser radar technology is an active remote sensing detection means, has the advantages of all-time and all-weather, is strong in anti-interference capability and high in resolution, can be used for obtaining three-dimensional point cloud of a target, and is widely applied to the fields of digital cities, automatic driving, topographic mapping and the like. Laser ranging is the core of laser radar technology, and the ranging precision directly influences the quality of the acquired target three-dimensional point cloud. The common laser radar ranging system measures the target distance based on a pulse ranging method, a laser transmits a beam of pulse with extremely short duration to a measured target object, a telescope receives a back reflection echo signal of the target object, and the distance between the target object and the laser radar ranging system is calculated according to the time difference between the transmitted pulse and the received pulse. The ranging precision of the laser radar ranging system comprises ranging precision and ranging accuracy, and mainly depends on the time measurement precision of the system, and the time measurement precision is related to the signal-to-noise ratio of a received signal and is influenced by factors such as the self characteristic of the system, the target characteristic and the environmental characteristic; meanwhile, different pulse time identification methods can cause different degrees of deviation, and the range finding deviation of the laser radar range finding system can be reduced by adopting a proper detection mode and a signal processing method, so that high-precision distance measurement is realized.
According to the data type of the processed pulse signal, the existing laser radar ranging technology can be divided into two types: analog ranging techniques and digital ranging techniques. The analog ranging technique is a pulse laser ranging technique commonly used at present, and based on an analog signal processing principle, Time interval measurement between a transmission pulse and an echo pulse is realized through a Time Digital Converter (Time Digital Converter). The analog ranging technology processes a pulse signal received by an optical system through an automatic gain technology, so that the amplitude of an echo pulse meets the requirement of an input voltage of a constant ratio timing circuit, the influence of echo amplitude difference on system ranging errors under different target distances is reduced, and the dynamic range of the system is improved; the constant ratio timing circuit realizes the determination of the laser pulse time point based on the constant ratio timing identification technology, and the determined pulse time point is insensitive to the change of the laser pulse amplitude value, thereby further overcoming the system ranging error caused by the echo amplitude value difference. The time-to-digital converter realizes the time interval measurement between the emission pulse and the echo pulse, thereby calculating the target distance, and the ranging precision of the system is limited by the time resolution of the time-to-digital converter. The automatic gain control technology adopted in the analog ranging technology is that the pulse amplitude of the previous moment is used for controlling and adjusting the pulse amplitude of the next moment, the problem of failure of the automatic gain control technology caused by sudden change of a target distance cannot be solved, the constant ratio timing circuit has high requirement on signal pulse waveform, and when the complexity of the pulse waveform is high, the constant ratio timing circuit is not applicable any more; meanwhile, the analog ranging technology ignores the target complex characteristics contained in the pulse waveform, and is difficult to overcome the problems of low multi-target identification rate and the like. To overcome the problems with the analog ranging technique, a digital ranging technique may be employed. The digital ranging technology is based on a high-speed acquisition technology, realizes high-speed synchronous acquisition of a transmitting waveform and a target echo waveform, and acquires characteristic parameters of a target in the low signal-to-noise ratio echo waveform through a waveform decomposition algorithm, thereby realizing accurate position acquisition of the target. In the digital ranging technology, the waveform output by the detector is generally processed by adopting a waveform decomposition algorithm, the problem of distance mutation in the automatic gain technology is solved while the dynamic range of the system is enlarged, and the waveform decomposition algorithm adopts a fitting mode to realize the extraction of a target distance, so that the sub-sampling ranging precision can be realized. According to different processing terminals of a waveform decomposition algorithm, the digital ranging technology is divided into a digital ranging post-processing technology and an online digital ranging technology. The digital ranging post-processing technology depends on a waveform decomposition algorithm on an upper computer and cannot extract target data in real time; the online digital distance measurement technology is based on a programmable processor and a digital waveform processing technology, and can realize online measurement of the target distance. The invention belongs to an online digital distance measurement technology.
According to the patent review provided by the prior patent office, the online Digital ranging technology can perform time domain registration analysis on a laser pulse Signal through a waveform processing method realized by programming based on one of a Field-Programmable Gate Array (Field-Programmable Gate Array) analysis module and a Digital Signal Processor (Digital Signal Processor) analysis module, and further realize real-time calculation of a target distance through an output result of the analysis module, wherein the above patent includes a pulse laser ranging system based on waveform time domain registration analysis disclosed in chinese patent CN 103364790A. However, in the method, the waveform data is acquired by adopting an analog-to-digital conversion device, the waveform time identification is directly carried out by utilizing the sampling point, a waveform online fitting method is not adopted, and the distance measurement precision is influenced by the waveform shape of the target laser pulse echo. The on-line waveform fitting method of the application patent needs to perform nonlinear exponential function operation, the nonlinear exponential function operation is usually realized by adopting an exponential function lookup table, the exponential function lookup table is constructed by establishing the relation between an exponential function and a variable address, and the exponential function operation is realized, and the patent comprises a coherent lognormal distribution radar clutter real-time simulation method disclosed in Chinese patent CN 107202979A. However, the step length is fixed when the index function lookup table is established, the resource problem is not considered, more computing resources of the programmable processor are occupied, and the real-time requirement of the waveform fitting algorithm in the online digital ranging technology cannot be met.
In order to solve the problem of failure of the automatic gain control technology caused by the sudden distance change of the analog ranging technology, the target characteristic parameter vector is extracted in real time, and the target distance measurement precision is improved. The invention discloses a laser radar waveform time identification method and an online ranging system, which realize high-speed multichannel synchronous acquisition of pulse signals based on an analog-to-digital conversion device, realize the time identification method by programming on an open programmable processor, perform high-speed online processing on echo signals and further realize real-time measurement of target distance. The system has strong development, can detect richer information of the target by designing different algorithms, and simultaneously extracts the characteristic function of the target in the echo with low signal-to-noise ratio by carrying out waveform decomposition on the signal waveform, thereby improving the ranging precision and dynamic range of the system and realizing the online high-precision measurement of the target distance. The invention has wide application prospect in the field of laser radar measurement.
Disclosure of Invention
The invention discloses a laser radar waveform time identification method and an online ranging system, which are characterized in that the laser radar waveform time identification method and the online ranging system are used for realizing the digital online processing of pulse signals based on a multi-channel high-speed analog-to-digital conversion device and a programmable processor; the pulse signal comprises the laser radar waveform time identification method, a transmitting pulse signal and an echo pulse signal in an online ranging system; the multichannel high-speed Analog-to-Digital conversion device consists of a plurality of configurable Analog-to-Digital converters (Analog-to-Digital converters), and is used for digitally collecting the pulse signals, recording emission pulse waveforms and echo pulse waveforms and realizing high-speed synchronous collection of multichannel laser pulse signals; the Programmable Processor includes, but is not limited to, a Field-Programmable Gate Array (Field-Programmable Gate Array), and/or a Complex Programmable Logic Device (Complex Programmable Logic Device), and/or an ARM Processor (Advanced RISC Machines), and/or a Digital Signal Processor (Digital Signal Processor), and implements high-speed online processing of the pulse waveform Signal based on the compiled waveform time identification method;
the laser radar time identification method and the ranging system comprise three parts: the device comprises a detection and receiving unit, a high-speed acquisition and processing unit and an upper computer unit; the detection and receiving unit is used for detecting the emission pulse signal, the echo pulse signal and the trigger pulse signal; the high-speed acquisition and processing unit comprises the multi-channel high-speed analog-to-digital conversion device, the programmable processor, an onboard memory and a high-speed computer parallel interface; the upper computer unit comprises a high-performance computing processing system and a receiving and storing software system;
the working process of the laser radar online ranging system is as follows: firstly, the programmable processor configures the multi-channel analog-to-digital conversion device to enable the multi-channel analog-to-digital conversion device to work under a specific sampling frequency, the detection and receiving unit generates the trigger pulse signal to trigger the programmable processor, and the programmable processor is triggered at a set sampling length NlInternal synchronous miningCollecting the emission pulse signal and the echo pulse signal, cutting a sampling waveform by the programmable processor through the waveform time identification method, and respectively performing online fitting on the emission pulse waveform and the echo pulse waveform by adopting a target function so as to extract pulse parameter information of the emission pulse waveform and the echo pulse waveform in real time, wherein the pulse parameter information comprises emission pulse intensity a1Position b of peak time of transmission pulse1And a transmission pulse width c1Echo pulse intensity a2Position b of peak time of echo pulse2And echo pulse width c2(ii) a Based on the waveform time identification method, the pulse parameter information is processed on line in the programmable processor, the time identification positions of the transmitted pulse signal and the echo pulse signal are respectively determined, the time position difference between the pulse signals is calculated, the target distance l is obtained through real-time calculation, and finally the target distance, the pulse parameter information, the acquired transmitted pulse waveform and the acquired echo pulse waveform are spliced and uploaded to the upper computer unit through the parallel interface of the high-speed computer to complete display and storage;
the waveform time identification method comprises the steps of searching a fitting initial value, cutting a transmitting waveform and an echo waveform, calculating an exponential function, calculating a Jacobian matrix and a residual vector, multiplying the matrix, solving the matrix to obtain an iteration step length, judging a convergence condition, calculating a target distance, splicing data and uploading; the algorithm of the transmitting pulse waveform is consistent with that of the echo pulse waveform, and the waveform time identification method is introduced by fitting the echo pulse waveform as an example and comprises the following steps:
1) determining the fitting initial value: according to the echo pulse waveform (x) received by the laser radar online distance measuring systemi,yi) Characterised by determining one of said objective functions f (x)i,βk)＝f(xi,(ak,bk,ck)T) Restoring a target characteristic, the target characteristic being determined by a characteristic parameter of the target function, the characteristic parameter being related to the pulse parameter information; the waveform time instant discrimination method selects a specific one of the objective functions,approximating the echo pulse waveform (x) based on an iterative method by online fittingi,yi) The characteristic parameter vector β of the objective function includes, but is not limited to, pulse intensity a, pulse peak time position b, and pulse width c; before the fitting algorithm starts, the initial fitting value needs to be determined, and the pulse intensity a is searched for through a discrete online peak position fast search algorithm0And the pulse peak time position b0The fitted initial value of the pulse width c is composed of an empirical value c as the fitted initial value of the pulse intensity a and the pulse peak time position b0Determining;
2) waveform cutting: the waveform cutting can eliminate useless noise information in the echo pulse waveform, so that the characteristic parameter vector is accurately obtained, the computing resource of the programmable processor is saved, and the operating efficiency of the waveform time identification method is improved; the waveform clipping is performed at the pulse peak time position b in step 10Searching N/2-1 sampling points on the left side, searching N/2 sampling points on the right side of the pulse peak time position in the step 1, and performing fitting by using N sampling points in total; the cutting length N is determined by the parameter characteristics of the pulse signal output by the detection and receiving unit;
3) and (3) calculating an exponential function: the objective function used for fitting usually comprises an exponential function exp (-x) taking a natural constant as a base, the exponential function taking the natural constant as the base needs to be circularly calculated in the fitting iteration process, and the waveform moment identification method adopts a variable step length online exponential function lookup table method based on the programmable processor and solves the exponential function taking the natural constant as the base in real time to meet the requirement of operation speed;
4) jacobi matrix (Jacobi matrix) and residual vector calculation: calculating residuals for each of the N clipped sample points during the kth fitting iteration, wherein the residuals for the ith sample point are calculated as:
ri＝yi-f(xi,βk) (1)
then, through the variable step length online exponential functionA number lookup table method for calculating the residual r on lineiIts partial derivatives with respect to the pulse intensity a, the pulse peak instant position b and the pulse width c; combining the residual error vector according to the residual error and the partial derivative obtained by calculation
And the Jacobian matrix J:
5) matrix multiplication: calculating the matrix A ═ J respectivelyTJ and
a calculation foundation is laid for solving the iteration step length h in the next step;
6) solving a matrix to solve an iteration step length: solving an equation Ah ═ B on line, and obtaining the iteration step length h in the waveform time identification method in real time; step 5), knowing that A is a 3-element square matrix and B is a 3-element vector, solving the equation Ah as B is to solve a one-dimensional ternary equation; solving the system of equations in a ternary linear form on-line based on the programmable processor including, but not limited to, Gaussian elimination, and/or trigonometric decomposition, and/or Jacobian iteration, and/or Gaussian-Seidel iteration, the result of the solution being the iteration step size
7) And (3) judging convergence conditions: for each iteration, the iteration counter k is automatically added with 1, and the iteration convergence condition is as follows: (1) the number of iterations is less than the maximum limit value k of the number of iterationsm(ii) a (2) The iteration step length reaches the convergence value epsilon, namely the (| | h | | | non-woven phosphor is judged<Whether epsilon is satisfied; if one of the convergence conditions is reached, stopping the iteration, and transferring to the step 8), or else, calculating the characteristic parameter vector beta in the next iterationk+1＝βk+ h, turning to the step 3), and performing the next iterative calculation;
8) calculating the target distance: the waveform time identification method carries out online fitting processing on the transmitted pulse waveform and the echo pulse waveform respectively, calculates the characteristic parameter vector in real time and obtains the transmitted pulse intensity a respectively1The peak time position b of the transmission pulse1Said transmission pulse width c1The intensity of the echo pulse a2The peak time position b of the echo pulse2And the echo pulse width c2The time discrimination method includes, but is not limited to, Peak time discrimination (Peak discrimination), and/or zero-crossing time discrimination, and/or Leading Edge time discrimination, and/or Center of Gravity discrimination, and/or Constant ratio timing discrimination (Constant ratio discrimination) to determine the time positions t of the transmit pulse signal and the echo pulse signal1And t2And calculating the time position difference delta t ═ t in real time2-t1Further obtain the target distance
9) Data splicing and uploading: finally, the data splicing and uploading work is carried out, the target distance data l and the emission pulse intensity a which are obtained by the calculation of the steps are obtained1The peak time position b of the transmission pulse1And the transmission pulse width c1The intensity of the echo pulse a2The peak time position b of the echo pulse2Said echo pulse width c2And splicing the transmitting pulse waveform and the echo pulse waveform, uploading to the upper computer unit through the high-speed parallel interface, and performing display and storage operation.
The laser radar waveform time identification method and the online ranging system are characterized in that a specific target function is determined according to the characteristics of the echo pulse waveform to serve as a fitting target function, and the characteristic parameter vectors are obtained online through the compiled fitting algorithm based on the programmable processor, wherein the characteristic parameter vectors include but are not limited to the pulse intensity a, the pulse peak time position b and the pulse width c; the objective function includes, but is not limited to, a gaussian model, and/or an erlang model, and/or a gaussian mixture model, and extracting more of the objective characteristics can be achieved by changing the number of elements of the characteristic parameter vector, which is selected in relation to the computational complexity of the programmable processor resource and the waveform time discrimination method.
The laser radar waveform moment identification method and the online ranging system are characterized in that the real-time calculation of the exponential function exp (-x) taking a natural constant as a base in the target function is realized by adopting the variable step length online exponential function lookup table method; the step length variable online index function lookup table is manufactured by manufacturing a series of result values of the index function with the base of a natural constant by utilizing a ROM (read only memory) resource of the programmable processor based on the programmable processor, acquiring a function result required by the waveform time identification method by calculating the corresponding relation between the index function with the base of the natural constant and the ROM address, wherein the corresponding relation is nonlinear correspondence, improving the precision of the step length variable online index function lookup table by introducing variable step length according to the target function, reducing the resource occupied by the step length variable online index function lookup table, and adjusting the calculation precision and the size not to exceed the ROM resource of the system by adjusting the variable step length of the step length variable online index function lookup table.
The laser radar waveform time identification method and the online ranging system are characterized in that the iteration step length is solved online based on the programmable processor, the iteration step length is calculated in real time so as to enable the selected initial value to gradually approach the optimal ranging value, the online calculation of the iteration step length is realized by solving the ternary linear equation set consisting of the target function and the measured data online, and the online solution of the equation set can be realized by using methods including but not limited to a Gaussian elimination method, and/or a trigonometric decomposition method, and/or a Jacobi iteration method, and/or a Gauss-Seidel iteration method; based on the programmable processor, the equation set is solved by adopting a parallel processing structure, and the iterative step length is solved on line; the selection of the equation system solving method is related to the programmable processor resource and the number of the iteration step size elements, and the number of the iteration step size elements is the same as the number of the elements of the characteristic parameter vector.
The laser radar waveform moment identification method and the online ranging system are characterized in that the detection and receiving unit is coupled with the high-speed acquisition and processing unit in parameter design; the distance measurement precision of the laser radar online distance measurement system is related to the number of sampling points of the pulse signal acquired by the high-speed acquisition and processing unit, the number of the sampling points is limited by the sampling rate of the multi-channel high-speed analog-to-digital conversion device and the pulse width output by the detection and receiving unit, the pulse width is determined by the laser emission pulse width and the detector bandwidth, the distance measurement precision requirement is guaranteed, the multi-channel high-speed analog-to-digital conversion device works in a high sampling rate mode, the selection of the laser emission pulse width and the detector bandwidth needs to be met, and the distance measurement precision requirement is limited by the minimum number of the sampling points in the high sampling rate mode.
The laser radar waveform moment identification method and the online ranging system are characterized in that the laser radar waveform moment identification method is designed based on the programmable processor resource and the sampling rate of the high-speed acquisition and processing unit; the calculation complexity of the laser radar waveform time identification method is related to the number of the sampling points and the number of elements of the characteristic parameter vector and the equation set solving method, the calculation complexity of the laser radar waveform time identification method can limit the distance measurement precision, and the design of the laser radar waveform time identification method needs to comprehensively consider the maximum calculation complexity of the algorithm and the required distance measurement precision which can be met by the programmable processor resources; meanwhile, in order to ensure that the distance measurement precision requires that the multichannel high-speed analog-to-digital conversion device works in a high sampling rate mode, the calculation rate requirement of the designed laser radar waveform moment identification method is matched with the sampling rate of the multichannel high-speed analog-to-digital conversion device, namely the calculation complexity meets the requirement of processing the output data of the multichannel high-speed analog-to-digital conversion device in real time, and data blockage and loss are prevented.
The laser radar waveform time identification method and the online ranging system are characterized in that target characteristic parameters including but not limited to target distance l, target inclination, target roughness and target elevation distribution are obtained through real-time calculation based on the programmable processor; the laser radar waveform moment identification method and the online ranging System can be used for carrying out cooperative measurement with an Inertial Navigation System (Inertial Navigation System), a Global Positioning System (Global Positioning System) and a laser scanning mechanism, and fusing the extracted target characteristic parameters with position and attitude information output by the Inertial Navigation System and the Global Positioning System and scanning angle information output by the laser scanning mechanism to realize online three-dimensional point cloud generation.
Drawings
FIG. 1 is a schematic diagram of a laser radar waveform time identification method and an on-line distance measurement system
FIG. 2 is a schematic diagram of a detecting and receiving unit
FIG. 3 is a schematic diagram of a high-speed acquisition and processing unit
FIG. 4 is a flow chart of the laser radar waveform time discrimination method and the on-line distance measuring system
FIG. 5 shows the results of laser pulse signal acquisition and fitting
FIG. 6 is a flow chart of a waveform time discrimination method
FIG. 7 is a schematic diagram of five time discrimination methods
FIG. 8 is a diagram of a simulation system for laser radar waveform time discrimination
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings.
The invention discloses a laser radar waveform time identification method and an online ranging system, and the specific structure of one embodiment of the system is shown in figure 1. The laser radar waveform time identification method and the online ranging system comprise three parts: a detection and receiving unit (as shown in fig. 2), a high-speed acquisition and processing unit (as shown in fig. 3), and an upper computer unit.
In this embodiment, the detecting and receiving unit is configured to detect the transmission pulse signal, the echo pulse signal, and the trigger pulse signal, and the specific structure of the detecting and receiving unit is shown in fig. 2. The pulse laser 102 in the detection and receiving unit is configured by the controller 101, and emits laser pulses at a certain pulse repetition frequency, and the laser pulses are divided into 3 laser pulses by the beam splitter 103 and the beam splitter 104; one laser pulse is detected by the trigger pulse detector 105 and then converted into the trigger pulse signal 113, the other laser pulse is attenuated by the attenuation sheet 106 and then detected by the emission pulse detector 107 and converted into the emission pulse signal 114, the last laser pulse is emitted through the coaxial module 108 and then enters the target 109, the laser pulse reflected by the target 109 returns to the coaxial module 108 and is received by the telescope in the coaxial module 108, and the background noise is filtered by the narrow-band filter 110 and then is detected by the echo pulse detector 111 and converted into the echo pulse signal 112.
The high-speed acquisition and processing unit is based on the programmable processor and is used for performing high-speed online processing on the transmission pulse signal and the echo pulse signal to acquire target distance information; the specific structure of the high-speed acquisition and processing unit is shown in fig. 3, and includes a high-speed analog-to-digital conversion device 204, a programmable processor 205 (in this embodiment, a field programmable gate array of a Virtex6 chip of Xilinx corporation is taken as an example), an onboard memory 207, and a high-speed computer parallel interface 206 (in this embodiment, a PCIE bus is taken as an example); the emission pulse channel 201, the echo pulse channel 202 and the trigger pulse channel 203 are respectively used for receiving the emission pulse signal 114, the echo pulse signal 112 and the trigger pulse signal 114 output by the detection and receiving unit; the multichannel high-speed analog-to-digital conversion device consists of a plurality of configurable analog-to-digital conversion devices 204, and when the multichannel high-speed analog-to-digital conversion device is triggered by the trigger pulse signal 114, the pulse signal is digitally acquired, the emission pulse signal 114 and the echo pulse signal 112 are recorded, and the high-speed synchronous acquisition of the multichannel laser pulse signal is realized; the Programmable Processor 205 includes, but is not limited to, a Field-Programmable Gate Array (Field-Programmable Gate Array), and/or a Complex Programmable Logic Device (Complex Programmable Logic Device), and/or an ARM Processor (Advanced RISC Machines), and/or a Digital Signal Processor (Digital Signal Processor), and implements high-speed online processing of the pulse waveform Signal based on the compiled waveform time identification method.
The upper computer unit in this embodiment includes a high-performance computer, receiving and storing software, and the like, and receives the target distance information and the pulse waveform signal information uploaded by the high-speed acquisition and processing unit through the high-speed computer parallel interface 206, so as to be used for subsequent three-dimensional laser point cloud online generation and three-dimensional laser point cloud post-processing generation research.
The working flow of the laser radar waveform time identification method and the online ranging system in the embodiment is shown in fig. 4: firstly, the programmable processor 205 configures the multi-channel analog-to-digital conversion device 204 to operate at a specific sampling frequency; then, the emission pulse signal 114 and the echo pulse signal 112 output by the detection and receiving unit are received by the high-speed acquisition and processing unit, and the high-speed acquisition and processing unit performs high-speed online processing on the pulse signal based on the programmable processor 205 and the waveform time discrimination method; the detection and receiving unit generates the trigger pulse signal 113 to trigger the programmable processor 205, and the programmable processor 205 controls the multi-channel analog-to-digital conversion device 204 to set the sampling length NlThe transmitting pulse signal 114 and the echo pulse signal 112 are acquired synchronously, and the acquired transmitting pulse signal 114 and the acquired echo pulse signal 112 are shown as sampling points in fig. 5; the programmable processor 205 then crops the sampled waveform by the waveform time discrimination method; then, performing online fitting processing on the clipped transmit pulse signal 114 and the clipped echo pulse signal 112 through an objective function, wherein a result of a fitted pulse signal curve is shown as a dotted line in fig. 5, and pulse parameter information of the transmit pulse waveform 114 and the echo pulse waveform 112, including transmit pulse intensity a, is obtained by performing real-time extraction through the online fitting processing1Position b of peak time of transmission pulse1And the emission pulsePunch width c1Echo pulse intensity a2Position b of peak time of echo pulse2And echo pulse width c2(ii) a Respectively determining the time positions of the transmitting pulse signal 114 and the echo pulse signal 112 by the waveform time identification method based on the extracted pulse parameter information; calculating the time position difference between the pulse signals based on the time positions of the two pulse signals, further calculating in real time to obtain a target distance l, and when the next trigger pulse signal 113 arrives, skipping the synchronous acquisition step by the laser radar waveform time identification method and the online ranging system to enter the next target distance calculation process; and finally, splicing the target distance, the pulse parameter information, the acquired emission pulse waveform 114 and the acquired echo pulse waveform 112, and uploading the information to the upper computer unit through the high-speed computer parallel interface 206 to finish displaying and storing.
In this embodiment, the waveform time identification method solves the pulse parameter information by an online fitting method, and for each pulse waveform (x) received by the laser radar online ranging systemi,yi) There is one of the objective functions to restore the target characteristics, which are determined by the characteristic parameters of the objective function, and the characteristic parameters are related to the pulse parameter information, which can be extracted in this embodiment, including, but not limited to, the intensity of the transmitted pulse a1Position b of peak time of transmission pulse1And a transmission pulse width c1Echo pulse intensity a2Position b of peak time of echo pulse2And echo pulse width c2(ii) a In this embodiment, the characteristic parameter vector β of the objective function selected by the waveform time identification method includes pulse intensity a, pulse peak time position b and pulse width c, and the pulse parameter information is obtained by selecting a specific objective function to be fitted and solved, including but not limited to a gaussian model, and/or an erlangs model, and/or a gaussian mixture model; in this embodiment, taking a gaussian model as an example, the set fitting objective function is:
the fitting algorithm in the waveform moment identification method is an optimized solving problem, the embodiment is based on the principle of least square algorithm, adopts the gauss-newton iteration method to solve, updates the parameter vector in each iteration by a certain iteration step length h, and calculates the fitting residual:
solving for a parameter vector β that minimizes the fitted residualkAs an estimate of the characteristic parameter vector beta. The flow chart of the waveform time identification method is shown in fig. 6, and comprises 9 parts: determining a fitting initial value, cutting a waveform, calculating an exponential function, calculating a Jacobian matrix and a residual vector, multiplying the matrix, solving an iteration step length, judging a convergence condition, calculating a target distance, splicing data and uploading; the detailed steps of the waveform time identification method are described as follows:
1) determining the fitting initial value: the waveform time identification method adopts an iteration method to perform online fitting approximation on the echo pulse waveform (x)i,yi) Before the fitting algorithm starts, the initial fitting value needs to be determined, and the pulse intensity a is searched for through a discrete online peak position fast search algorithm0And the pulse peak time position b0As the fitting initial values of the pulse intensity a and the pulse peak time position b, the discrete online peak position fast search algorithm is based on gaussian model symmetry, a shift register is arranged in the programmable processor 205 to store waveforms in real time, a first-order difference value of every two adjacent sampling points in the shift register is calculated in parallel, and a first-order zero-crossing point of the gaussian model is found as a pulse peak initial point by judging the distribution of the first-order difference value; said fitted initial value of said pulse width c is determined from a measured empirical value c0Determining;
2) waveform cutting: the waveform moment identification method eliminates noise information in the echo pulse waveform through waveform cutting, saves the computing resource of the programmable processor 205, and improves the time efficiency of the algorithm; the waveform clipping is performed at the pulse peak time position b in step 10Searching N/2-1 sampling points on the left side, searching N/2 sampling points on the right side of the pulse peak time position in the step 1, and splicing the N sampling points into a cut fitting waveform; the clipping length N is determined by the parameter characteristics of the pulse signal output by the detecting and receiving unit and the computing resources of the programmable processor 205, in this embodiment, the pulse width is about 10 sampling points, and the selected clipping length is 40;
3) and (3) calculating an exponential function: the waveform moment identification method selects a Gaussian model as a fitting objective function, the objective function comprises an exponential function with a natural constant as a base, and the exponential function with the natural constant as the base needs to be circularly calculated in the fitting iteration process; the waveform moment identification method adopts a variable step length online exponential function lookup table method based on the programmable processor 205, and solves an exponential function with a natural constant as a base in real time to meet the requirement of operation speed; the step-variable online index function lookup table method is based on the programmable processor 205, utilizes the ROM resource of the onboard memory 207 in the programmable processor 205 to make a series of result values of the index function with the natural constant as the base, and obtains a function result required by the waveform time identification method by calculating the nonlinear corresponding relationship between the index function with the natural constant as the base and the ROM storage address, so as to realize the calculation of the index function on the programmable processor 205; the size of the variable-step online index function lookup table is related to the value step of the discrete index function variable, a variable step is introduced according to the target function, the value step is changed in real time in the value process of the discrete index function variable, the nonlinear correspondence between the index function variable and a storage address is realized, the calculation precision of the variable-step online index function lookup table is improved, the resource consumption of the variable-step online index function lookup table is reduced, the calculation precision and the size do not exceed the ROM resource of the system by adjusting the variable step of the variable-step online index function lookup table, and the waveform time identification method meets the resource limitation of the programmable processor 205;
4) jacobi matrix (Jacobi matrix) and residual vector calculation: parallel computing the residual r of each of the 40 samples clipped during the kth fitting iterationi(ii) a Then, the residual error r is calculated on line in parallel by the variable step length on-line exponential function lookup table methodiFor the pulse intensity a, the partial derivative of the pulse peak time position b and the pulse width c, and combining the calculated residual error and the partial derivative to obtain the residual error vector
And the Jacobian matrix J:
5) matrix multiplication: the waveform moment identification method needs to calculate iteration step length in real time in the fitting process, and according to the selected Gauss-Newton iteration algorithm, in order to solve the iteration step length h, firstly, a matrix A is required to be calculated to be JTJ and
realizing parallel computation of the matrix elements based on the programmable processor 205, and splicing the matrix elements to obtain the matrix;
6) iterative step size solving: the waveform time identification method obtains the iteration step length in the waveform time identification method in real time by solving an equation Ah ═ B on line
Step 5), knowing that A is a 3-element square matrix and B is a 3-element vector, solving the equation Ah as B is to solve a one-dimensional ternary equation; methods that can be used for the on-line solution of the system of equations include, but are not limited to, Gaussian elimination, andor trigonometric decomposition, and/or jacobian iteration, and/or gaussian-seidel iteration; in this embodiment, the online gaussian elimination method based on the programmable processor is used to solve the system of equations of three-dimensional equation in one time online, and the result of the solution is the iteration step length; the online Gaussian elimination method is based on the principle of the Gaussian elimination method, the elimination coefficient of each row and the matrix value after elimination are calculated in parallel, the original coefficient matrix is converted into a triangular matrix, and finally three parameter values in the iteration step length are solved in parallel through a substitution method and are combined to obtain the iteration step length;
7) and (3) judging convergence conditions: in each iteration in the waveform moment identification method, an iteration counter k is automatically added with 1, and the iteration convergence condition is as follows: (1) the number of iterations is less than the maximum limit value k of the number of iterationsm(ii) a (2) The iteration step length reaches the convergence value epsilon, namely the (| | h | | | non-woven phosphor is judged<Whether epsilon is satisfied; the maximum limit value k of the iteration numbermThe establishment of (1) prevents the calculation from entering a dead loop, in the embodiment, in order to ensure the operation efficiency of the algorithm, the maximum limit value of the iteration times is 5; if one of the convergence conditions is reached, stopping the iteration, and transferring to the step 8), or else, calculating the characteristic parameter vector beta in the next iterationk+1＝βk+ h, turning to the step 3), and performing the next iterative calculation;
8) calculating the target distance: the waveform time identification method carries out online fitting processing on the transmitted pulse waveform and the echo pulse waveform respectively, calculates the characteristic parameter vector in real time and obtains the transmitted pulse intensity a respectively1The peak time position b of the transmission pulse1Said transmission pulse width c1The intensity of the echo pulse a2The peak time position b of the echo pulse2And the echo pulse width c2(ii) a The reuse timing discrimination methods (as shown in FIG. 7) include, but are not limited to, Leading Edge timing discrimination 401(Leading Edge discrimination), and/or Constant Fraction timing discrimination 402(Constant Fraction discrimination), and/or zero crossing timing discrimination 403 (reflection discrimination), and/or Peak timing discrimination 404(Peak discrimination), and/or Center of Gravity discrimination 405(Center of Gravity discrimination)An interpolator) for determining the transmit time instant position t of the transmit pulse signal and the echo pulse signal1(301 in FIG. 5) and echo time position t2(302 in fig. 5), calculating the time position difference Δ t-t in real time according to the set sampling frequency of the multichannel analog-to-digital conversion device 2042-t1Further obtain the target distance
9) Data splicing and uploading: finally, the target distance data l and the emission pulse intensity a obtained by the calculation of the steps are calculated1The peak time position b of the transmission pulse1And the transmission pulse width c1The intensity of the echo pulse a2The peak time position b of the echo pulse2Said echo pulse width c2And the transmitting pulse waveform and the echo pulse waveform are spliced and then uploaded to the upper computer unit through the high-speed parallel interface 206 to be displayed and stored.
In this embodiment, the waveform time discrimination method is subjected to function simulation, and the simulation program is composed of a program to be tested and a test bench program. The program to be tested is a fitting program adopting a fixed point number format, the input of the program comprises a data input din, a clock signal clk and a reset signal rst, and the output of the program to be tested is fitting parameters a, b and c and a fitting ending signal r. The function of the test station program is to generate input data, clock signal and reset signal, and to receive and display fitting parameters and fitting end signal from the program to be tested, and the structure diagram of the simulation program is shown in fig. 8. The input data is laser pulse waveform data acquired through experiments, the pulse amplitude, the width, the shape and the noise of the laser pulse waveform data are similar to those of the laser radar waveform time identification method and the online ranging system, and the accuracy, the operation time and other performances of the waveform time identification method in processing the pulse waveform data can be verified. And performing Gaussian fitting on test data by using a Matlab fitting algorithm and the waveform time identification method respectively in the simulation experiment, taking a Matlab generated result as a reference true value, and calculating the relative error of the calculation result of the waveform time identification method. The simulation result is shown in table 1, the simulation result shows that the deviation of the waveform time identification method is within 1.5%, the precision requirement of the online digital ranging technology can be met, and the operation time is far shorter than the Matlab fitting algorithm.
TABLE 1Matlab fitting Algorithm and simulation results of waveform time discrimination method
| Fitting results | Matlab | Programmable processor | Relative error |
| a/mV | 75.0773 | 75.3146 | 0.4％ |
| b/ns | 232.4105 | 235.4184 | 1.3％ |
| c/ns | 6.3459 | 6.2647 | 1.3％ |
| Operation time | 473.3s | 0.06ms |
In the laser radar waveform time identification method and the online ranging system in the embodiment, based on the multi-channel analog-to-digital conversion device 204 and the programmable processor 205, target characteristic parameters including, but not limited to, a target distance l, a target inclination, a target roughness and a target elevation distribution are obtained through real-time calculation; the laser radar waveform time identification method and the online ranging System can be cooperatively measured with an Inertial Navigation System (Inertial Navigation System), a Global Positioning System (Global Positioning System) and a laser scanning mechanism, and the target characteristic parameters extracted by the laser radar waveform time identification method and the online ranging System are fused with the Inertial Navigation System, the position and attitude information output by the Global Positioning System and the scanning angle information output by the laser scanning mechanism, so that online three-dimensional point cloud generation is realized.
The above description is only a basic scheme of the specific implementation method of the present invention, but the protection scope of the present invention is not limited thereto, and any changes and substitutions that can be conceived by those skilled in the art within the technical scope of the present invention are included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.
Claims (7)
1. A laser radar waveform time identification and online ranging system is characterized in that a laser radar waveform time identification method and a ranging system for realizing pulse signal digital online processing are realized based on a multi-channel high-speed analog-to-digital conversion device and a programmable processor; the pulse signals comprise transmitting pulse signals and echo pulse signals in the laser radar waveform time identification and online ranging system; the multichannel high-speed Analog-to-Digital conversion device consists of a plurality of configurable Analog-to-Digital converters (Analog-to-Digital converters), and is used for digitally collecting the pulse signals, recording emission pulse waveforms and echo pulse waveforms and realizing high-speed synchronous collection of multichannel laser pulse signals; the Programmable Processor comprises a Field-Programmable Gate Array (Field-Programmable Gate Array), and/or a Complex Programmable Logic Device (Complex Programmable Logic Device), and/or an Advanced RISC machine (Advanced RISC Machines), and/or a Digital Signal Processor (Digital Signal Processor), and realizes high-speed online processing of the pulse waveform Signal based on the compiled waveform time identification method;
the laser radar waveform moment identification and online ranging system comprises three parts: the device comprises a detection and receiving unit, a high-speed acquisition and processing unit and an upper computer unit; the detection and receiving unit is used for detecting the emission pulse signal, the echo pulse signal and the trigger pulse signal; the high-speed acquisition and processing unit comprises the multi-channel high-speed analog-to-digital conversion device, the programmable processor, an onboard memory and a high-speed computer parallel interface; the upper computer unit comprises a high-performance computing processing system and a receiving and storing software system;
the working process of the laser radar online ranging system is as follows: firstly, the programmable processor configures the multichannel high-speed analog-to-digital conversion device to enable the multichannel high-speed analog-to-digital conversion device to work under a specific sampling frequency, the detection and receiving unit generates the trigger pulse signal to trigger the programmable processor, and the programmable processor is triggered at a set sampling length NlThe method comprises the steps of internally and synchronously acquiring the transmitting pulse signal and the echo pulse signal, cutting a sampling waveform by the programmable processor through the waveform time identification method, and respectively performing online fitting on the transmitting pulse waveform and the echo pulse waveform by adopting a target function so as to extract pulse parameter information of the transmitting pulse waveform and the echo pulse waveform in real time, wherein the pulse parameter information comprises transmitting pulse intensity a1Position b of peak time of transmission pulse1And a transmission pulse width c1Echo pulse intensity a2Position b of peak time of echo pulse2And echo pulse width c2(ii) a Based on the waveform time identification method, the pulse parameter information is processed by the programmable processorOn-line processing, namely respectively determining time identification positions of the transmitting pulse signal and the echo pulse signal, calculating a time position difference between the pulse signals, calculating a target distance l in real time, finally splicing the target distance, the pulse parameter information, the acquired transmitting pulse waveform and the acquired echo pulse waveform, and uploading the spliced transmitting pulse waveform and the acquired echo pulse waveform to the upper computer unit through a parallel interface of the high-speed computer to finish displaying and storing;
the waveform time identification method comprises the steps of searching a fitting initial value, cutting a transmitting waveform and an echo waveform, calculating an exponential function, calculating a Jacobian matrix and a residual vector, multiplying the matrix, solving the matrix to obtain an iteration step length, judging a convergence condition, calculating a target distance, splicing data and uploading; the algorithm of the transmitting pulse waveform is consistent with that of the echo pulse waveform, and the waveform time identification method is introduced by fitting the echo pulse waveform as an example and comprises the following steps:
1) determining the fitting initial value: according to the echo pulse waveform (x) received by the laser radar online distance measuring systemi,yi) Characterised by determining one of said objective functions f (x)i,βk)＝f(xi,(ak,bk,ck)T) Restoring a target characteristic, the target characteristic being determined by a characteristic parameter of the target function, the characteristic parameter being related to the pulse parameter information; the waveform time identification method is characterized in that a specific target function is selected, and the echo pulse waveform (x) is approximated by online fitting based on an iteration methodi,yi) The characteristic parameter vector beta of the objective function comprises pulse intensity a, pulse peak time position b and pulse width c; before the fitting algorithm starts, the initial fitting value needs to be determined, and the pulse intensity a is searched for through a discrete online peak position fast search algorithm0And the pulse peak time position b0The fitted initial value of the pulse width c is composed of an empirical value c as the fitted initial value of the pulse intensity a and the pulse peak time position b0Determining;
2) waveform cutting: the waveform cutting can eliminate the echo pulse waveUseless noise information in the waveform is obtained, so that the characteristic parameter vector is accurately obtained, the computing resource of the programmable processor is saved, and the operating efficiency of the waveform moment identification method is improved; the waveform clipping is performed at the pulse peak time position b in step 10Searching N/2-1 sampling points on the left side, searching N/2 sampling points on the right side of the pulse peak time position in the step 1, and performing fitting by using N sampling points in total; the cutting length N is determined by the parameter characteristics of the pulse signal output by the detection and receiving unit;
3) and (3) calculating an exponential function: the objective function used for fitting usually comprises an exponential function exp (-x) taking a natural constant as a base, the exponential function taking the natural constant as the base needs to be circularly calculated in the fitting iteration process, and the waveform moment identification method adopts a variable step length online exponential function lookup table method based on the programmable processor and solves the exponential function taking the natural constant as the base in real time to meet the requirement of operation speed;
4) jacobi matrix (Jacobi matrix) and residual vector calculation: calculating residuals for each of the N clipped sample points during the kth fitting iteration, wherein the residuals for the ith sample point are calculated as:
ri＝yi-f(xi,βk) (1)
then, the residual errors r are respectively calculated on line through the variable step length on-line exponential function lookup table methodiIts partial derivatives with respect to the pulse intensity a, the pulse peak instant position b and the pulse width c; combining the residual error vector according to the residual error and the partial derivative obtained by calculation
And the Jacobian matrix J:
5) matrix multiplication: respectively calculate momentsArray A ═ JTJ and
a calculation foundation is laid for solving the iteration step length h in the next step;
6) solving a matrix to solve an iteration step length: solving an equation Ah ═ B on line, and obtaining the iteration step length h in the waveform time identification method in real time; step 5), knowing that A is a 3-element square matrix and B is a 3-element vector, solving the equation Ah as B is to solve a one-dimensional equation set; on the basis of the programmable processor, solving the ternary linear equation set on line, wherein the result of the solution is the iteration step size
7) And (3) judging convergence conditions: for each iteration, the iteration counter k is automatically added with 1, and the iteration convergence condition is as follows: (1) the number of iterations is less than the maximum limit value k of the number of iterationsm(ii) a (2) The iteration step length reaches a convergence value epsilon, namely whether the condition that h < epsilon is met is judged; if one of the convergence conditions is reached, stopping the iteration, and transferring to the step 8), or else, calculating the characteristic parameter vector beta in the next iterationk+1＝βk+ h, turning to the step 3), and performing the next iterative calculation;
8) calculating the target distance: the waveform time identification method carries out online fitting processing on the transmitted pulse waveform and the echo pulse waveform respectively, calculates the characteristic parameter vector in real time and obtains the transmitted pulse intensity a respectively1The peak time position b of the transmission pulse1Said transmission pulse width c1The intensity of the echo pulse a2The peak time position b of the echo pulse2And the echo pulse width c2The time discrimination method comprises Peak time discrimination (Peak discrimination), and/or zero-crossing time discrimination (deflection discrimination), and/or Leading Edge discrimination, and/or barycentric time discrimination (Center of Gravity discrimination), and/or Constant ratio timing discrimination (Constant Fraction discrimination)Determining the time position t of the emission pulse signal and the echo pulse signal1And t2And calculating the time position difference delta t ═ t in real time2-t1Further obtain the target distance
9) Data splicing and uploading: finally, the data splicing and uploading work is carried out, the target distance data l and the emission pulse intensity a which are obtained by the calculation of the steps are obtained1The peak time position b of the transmission pulse1And the transmission pulse width c1The intensity of the echo pulse a2The peak time position b of the echo pulse2Said echo pulse width c2And splicing the transmitting pulse waveform and the echo pulse waveform, uploading to the upper computer unit through a high-speed parallel interface, and performing display and storage operations.
2. The lidar waveform time discrimination and online ranging system according to claim 1, wherein a specific objective function is determined as a fitting objective function according to the characteristics of the echo pulse waveform, and the characteristic parameter vector is obtained online by the compiled fitting algorithm based on the programmable processor, and comprises the pulse intensity a, the pulse peak time position b and the pulse width c; the target function comprises a Gaussian model and/or an Irish model and/or a Gaussian mixture model, more target characteristics can be extracted by changing the number of elements of the characteristic parameter vector, and the number of elements of the characteristic parameter vector is selected to be related to the computation complexity of the programmable processor resource and the waveform time identification method.
3. The system for laser radar waveform moment discrimination and online ranging according to claim 1, wherein real-time calculation of the exponential function exp (-x) based on a natural constant in the objective function is achieved by using the variable step length online exponential function lookup table method; the step length variable online index function lookup table is manufactured by manufacturing a series of result values of the index function with the base of a natural constant by utilizing a ROM (read only memory) resource of the programmable processor based on the programmable processor, acquiring a function result required by the waveform time identification method by calculating the corresponding relation between the index function with the base of the natural constant and the ROM address, wherein the corresponding relation is nonlinear correspondence, improving the precision of the step length variable online index function lookup table by introducing variable step length according to the target function, reducing the resource occupied by the step length variable online index function lookup table, and adjusting the calculation precision and the size not to exceed the ROM resource of the system by adjusting the variable step length of the step length variable online index function lookup table.
4. The lidar waveform time identification and online ranging system according to claim 1, wherein the iterative step is calculated in real time based on online solving of the iterative step by the programmable processor, the iterative step is calculated in order to gradually approximate the selected initial value to an optimal ranging value, the iterative step is calculated online by solving the system of equations of the ternary linear system of the objective function and the measurement data online, and the method for online solving of the system of equations can be used including gaussian elimination, and/or trigonometric decomposition, and/or jacobian iteration, and/or gaussian-seidel iteration; based on the programmable processor, the equation set is solved by adopting a parallel processing structure, and the iterative step length is solved on line; the selection of the equation system solving method is related to the programmable processor resource and the number of the iteration step size elements, and the number of the iteration step size elements is the same as the number of the elements of the characteristic parameter vector.
5. The lidar waveform time discrimination and online ranging system of claim 1, wherein a parametric design coupling between the detection and receiving unit and the high speed acquisition and processing unit; the distance measurement precision of the laser radar online distance measurement system is related to the number of sampling points of the pulse signal acquired by the high-speed acquisition and processing unit, the number of the sampling points is limited by the sampling rate of the multi-channel high-speed analog-to-digital conversion device and the pulse width output by the detection and receiving unit, the pulse width is determined by the laser emission pulse width and the detector bandwidth, the distance measurement precision requirement is guaranteed, the multi-channel high-speed analog-to-digital conversion device works in a high sampling rate mode, the selection of the laser emission pulse width and the detector bandwidth needs to be met, and the distance measurement precision requirement is limited by the minimum number of the sampling points in the high sampling rate mode.
6. The lidar waveform time discrimination and online ranging system of claim 1, wherein the lidar waveform time discrimination method is designed based on the programmable processor resources and a sampling rate of the high-speed acquisition and processing unit; the calculation complexity of the laser radar waveform time identification method is related to the number of sampling points and the number of elements of the characteristic parameter vector and the equation set solving method, the calculation complexity of the laser radar waveform time identification method can limit the measurement precision of the target distance l, and the design of the laser radar waveform time identification method needs to comprehensively consider the maximum calculation complexity of the algorithm and the required distance measurement precision which can be met by the programmable processor resources; meanwhile, in order to ensure that the distance measurement precision requires that the multichannel high-speed analog-to-digital conversion device works in a high sampling rate mode, the calculation rate requirement of the designed laser radar waveform moment identification method is matched with the sampling rate of the multichannel high-speed analog-to-digital conversion device, namely the calculation complexity meets the requirement of processing the output data of the multichannel high-speed analog-to-digital conversion device in real time, and data blockage and loss are prevented.
7. The lidar waveform time discrimination and online ranging system according to claim 1, wherein the target characteristic parameters including target distance l, target inclination, target roughness, and target elevation distribution are calculated in real time based on the programmable processor; the laser radar waveform moment identification method and the online ranging System can be used for carrying out cooperative measurement with an Inertial Navigation System (Inertial Navigation System), a Global Positioning System (Global Positioning System) and a laser scanning mechanism, and fusing the extracted target characteristic parameters with position and attitude information output by the Inertial Navigation System and the Global Positioning System and scanning angle information output by the laser scanning mechanism to realize online three-dimensional point cloud generation.
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