Fuzzy ranging reconstruction method and system

Abstract

The invention provides a fuzzy ranging reconstruction method and system, and the method comprises the steps: modulating the pulse frequency of seed light transmitted by a laser radar through employing a floating step frequency modulation strategy, randomly selecting the transmission time interval between adjacent seed light in a prefabricated set, and enabling the time modulation amounts between the adjacent seed light to be unequal, the emitted seed light carries ranging noise; a seed light sequence of pulse emission and a return light sequence reflected by a target are stored respectively, the seed light sequence is the time difference between the current seed light and the previous seed light, and the return light sequence is the time difference between the current return light and the nearest seed light; and according to the distance measurement continuity and frequency modulation step characteristics of the return light sequences, through sequence segmentation, period hypothesis and verification and mask intensity calculation, emission periods to which the return light sequences belong are automatically judged, and a real distance value is reconstructed. According to the invention, full-automatic cross-cycle identification without manual intervention is realized, and the integrity and accuracy of the point cloud data are improved.

Description

Technical Field

[0001] This invention relates to the field of pulsed laser ranging technology, and specifically to a fuzzy ranging reconstruction method and system. Background Technology

[0002] The basic principle of pulsed lidar is to emit a laser pulse signal and receive the pulse signal reflected by the target. By measuring the time difference between the emitted and received pulses and combining this with the speed of light, the distance between the transmitter and the target is determined. The laser pulse emitted by the lidar is called the seed light, and the laser pulse reflected by the target is called the return light. The farther the target is, the longer the time interval between the seed light and the return light. The time interval between two adjacent seed light pulses is called the seed light emission period, which is equal to the reciprocal of the seed light emission frequency. As the ranging increases and the seed light emission frequency increases, there will inevitably be situations where a new seed light has already been emitted before the return light corresponding to the seed light arrives at the lidar. This makes it impossible to determine the true ranging value, resulting in fuzzy ranging, i.e., there is one or more seed light pulses between the return light pulse and its corresponding seed light.

[0003] Traditional methods for solving the problem of fuzzy ranging in lidar mainly include: 1. Limiting the ranging range to distribute the return light period within a defined range. This method has high limitations on application scenarios, and data processing requires manually specifying the return light period; 2. Giving the return light period to different angle ranges based on the first line scan data, and then judging the return light period of subsequent measurement results based on the continuity of point cloud data. This method also requires manual intervention and has limited applicability; 3. Encoding the seed light to give the return light a periodic marker. This method has a high degree of automation and can adapt to various scenarios, but it is prone to point loss and misjudgment in cross-period regions.

[0004] To address the aforementioned technical challenges, this invention proposes a fuzzy ranging reconstruction method and system, which includes a seed light frequency conversion method, a data recording method, and a ranging reconstruction method, thereby resolving the fuzzy ranging problem caused by the cross-cycle phenomenon of laser radar backlight. Summary of the Invention

[0005] The main objective of this invention is to provide a fuzzy ranging reconstruction method and system to solve the problems of missed points and misjudgments in cross-cycle ranging as the ranging increases and the seed light emission frequency increases, as well as the need for manual intervention.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A fuzzy ranging reconstruction method includes the following steps: S1. A floating step frequency modulation strategy is used to modulate the frequency of the seed light pulse emitted by the lidar. The time interval between the emission of adjacent seed lights is randomly selected from a pre-made set, and the time modulation amount between adjacent seed lights is not equal. S2. Store the seed light sequence of the pulse emission and the back light sequence reflected by the target separately. The seed light sequence is the time difference between the current seed light and the previous seed light, and the back light sequence is the time difference between the current back light and its nearest seed light. S3. Based on the continuity of ranging and the frequency modulation step characteristics, the return light sequence is segmented and the emission period to which the return light sequence belongs is determined; S4. Based on the solved backlight period, combined with the speed of light and time difference, the distance measurement value is reconstructed.

[0007] Furthermore, in step S1, the frequency modulation amplitude of the floating step frequency modulation is... The transmission time of each pulse is delayed or advanced based on the current cycle.

[0008] Furthermore, step S1 also includes setting the basic frequency modulation step size. And several frequency modulation steps N, basic frequency modulation step size The frequency modulation amplitude of the floating stepped frequency modulation is determined by the scanning frequency of the lidar. In prefabricated sets Randomly selected from the base frequency modulation step size. Several frequency modulation steps N are used to control the time modulation range between adjacent measurement points in order to suppress distance ambiguity.

[0009] Furthermore, the basic frequency modulation step size The product of the frequency modulation step N numbers corresponds to the maximum ranging noise value between two adjacent measurement points.

[0010] Furthermore, in step S2, the seed light sequence of the pulse emission is stored, and only the seed light within the first n sweep cycles before the return light is stored, where the value of n is equal to the maximum number of return light cycles supported by the lidar.

[0011] Furthermore, in step S3, the segmentation of the backlight sequence is based on the following criteria: if the difference between the ranging values ​​of two adjacent valid backlight sequences is less than a first threshold, and the number of discontinuities in these two valid backlight sequences is less than a second threshold, they are divided into the same data segment; otherwise, a segmentation operation is performed.

[0012] Furthermore, the first threshold value is set to be slightly greater than the maximum ranging noise value, while the second threshold value is set according to the scanning frequency and scanning rotation speed parameters of the lidar.

[0013] Furthermore, in step S3, determining the emission period to which the return light sequence belongs includes the following steps: Several ranging sequences under assumed reverberation periods are constructed. In the ranging sequences, it is checked whether there are at least 5 consecutive points where the absolute value of the ranging change is less than the continuity judgment threshold. The continuity judgment threshold is set according to the lidar parameters and the scanning scene. If such a sequence exists, it proves that the assumed reverberation period is correct; otherwise, it proves that the assumption is incorrect. The correct reverberation period is used as the starting period of the ranging sequence in which these points are located, and the period of the remaining points is confirmed by expanding point by point based on this.

[0014] Furthermore, for the reflection points that fail the continuity judgment, a mask with a length of not less than 5 is set, and the sum of the squares of the distance difference between adjacent points under different reflection periods is calculated as the difference intensity. The point with the smallest difference intensity that is below a set threshold is selected. The reverberation period is used as the final judgment result, and a threshold is set. The value is equal to the basic frequency modulation step size. .

[0015] A second aspect of the present invention also provides a fuzzy ranging reconstruction system, including... The seed light modulation module is used to control the lidar to emit pulses according to a floating stepped frequency modulation strategy; Data storage module, used to record seed light sequence and backlight sequence; The data processing module is used to perform backlight sequence segmentation, period determination, and ranging reconstruction. The data output module is used to output point cloud data containing real distance information.

[0016] Compared with the prior art, the beneficial effects of the present invention are: The fuzzy ranging reconstruction method and system proposed in this application fine-tunes the emission time of the seed light emitted by the lidar by using a floating step frequency modulation method. This allows the seed light to carry a set ranging noise. By storing the seed light and the return light sequence separately, and then segmenting the return light sequence and automatically determining the period, combined with the speed of light calculation, cross-period recognition without manual intervention is achieved, improving the integrity and accuracy of point cloud data, and reconstructing the true ranging value. Attached Figure Description

[0017] The present invention will be further described below with reference to the accompanying drawings: Figure 1 This is a flowchart of a fuzzy ranging reconstruction method according to the present invention; Figure 2 This is a schematic diagram of the seed light sequence before and after frequency modulation according to the present invention. Detailed Implementation

[0018] Example 1 As attached Figure 1 As shown, a fuzzy ranging reconstruction method includes the following steps: S1. A floating step frequency modulation strategy is used to modulate the frequency of the seed light pulse emitted by the lidar. The frequency modulation amplitude of the floating step frequency modulation is... , attached Figure 2 As shown, the transmission time of each pulse is delayed or advanced based on the current cycle; the basic frequency modulation step size is set. And several frequency modulation steps N, basic frequency modulation step size The frequency modulation amplitude of the floating stepped frequency modulation is determined by the scanning frequency of the lidar. In prefabricated sets Randomly selected from the base frequency modulation step size Several frequency modulation steps N are used to control the time modulation range between adjacent measurement points to suppress distance ambiguity; the time interval between the emission of adjacent seed lights is randomly selected from a pre-made set, and the time modulation amounts between adjacent seed lights are not equal, i.e. This embodiment sets the basic frequency modulation step size. It is divided into 5 frequency modulation steps. The change in the single pulse emission time in the set The values ​​are selected from the options provided, where negative values ​​indicate an earlier pulse transmission time and positive values ​​indicate a later pulse transmission time. .

[0019] S2. Store the seed light sequence of the pulse emission and the back light sequence reflected by the target separately. The seed light sequence is the time difference between the current seed light and the previous seed light, and the back light sequence is the time difference between the current back light and its nearest seed light. Meanwhile, in storing the seed light sequence, it is not necessary to store all seed lights; only the seed lights within the n sweep cycles before the return light appears are selected for storage, thus avoiding invalid seed light sequences occupying additional data storage space. The selection of n is equal to the maximum return light span range supported by the data. For example, at a certain scanning frequency, the number of return light spans corresponding to the maximum ranging is 5, so n=5 is chosen.

[0020] In addition to storing the aforementioned ranging sequence, the raw data should also store other data that may be included in each measurement cycle, such as intensity data, absolute time data, angle data, and quality factor data. A set of seed light sequences and backlight sequences can be written in the following form: ; Indicates the seed light sequence. The backlight sequence represents the seed light sequence, which is continuous, while the backlight sequence may be discontinuous. When no backlight is detected within a transmission cycle, the backlight sequence value corresponding to that cycle is set to 0. In the cross-cycle data analysis of lidar, the cycle in which the backlight is 0 is called the discontinuous cycle.

[0021] S3. Based on the continuity of ranging and the frequency modulation step characteristics, the return light sequence is segmented and the emission period to which the return light sequence belongs is determined; The segmentation of the return light sequence is based on the following criteria: if the difference in ranging values ​​between two adjacent valid return light sequences is less than a first threshold, and the number of discontinuities in these two valid return light sequences is less than a second threshold, they are divided into the same data segment; otherwise, segmentation is performed. The first threshold is set slightly higher than the maximum ranging noise value. The second threshold is set according to the scanning frequency and rotation speed parameters of the lidar. A higher lidar scanning frequency results in a larger second threshold; conversely, a higher rotation speed results in a smaller second threshold. The actual value is adjusted reasonably to balance these two factors. Generally, when the lidar scanning frequency is 1000 kHz and the rotation speed is 100 rps, the second threshold can be set to 50.

[0022] Determining the emission period of the return light sequence involves the following steps: First, construct several ranging sequences under assumed return light periods. Then, check if there are at least five consecutive points in the ranging sequence where the absolute value of the ranging change is less than a continuity threshold. This continuity threshold is set based on the lidar parameters and the scanning scene. If such a sequence exists, the assumed return light period is correct; otherwise, the assumption is incorrect. The correct return light period can be used as the starting period of the ranging sequence for these points, and this period is then used to expand point by point to confirm the period assignment of the remaining points.

[0023] For the reverberation points that fail the continuity test, a mask with a length of not less than 5 is set up. The sum of the squares of the distance differences between adjacent points under different reverberation periods is calculated as the difference intensity. The point with the smallest difference intensity that is below a set threshold is selected. The reverberation period is used as the final judgment result, and a threshold is set. The value is equal to the basic frequency modulation step size. .

[0024] Discrete echo points that still cannot be assigned to any period are marked as noise and discarded.

[0025] S4. Based on the solved retrograde period, combined with the speed of light and time difference, the ranging value is reconstructed. For example, the formula for calculating the retrograde ranging value within periods 1-4 is as follows: ; Where c is the speed of light under the current conditions.

[0026] Example 2 Based on Example 1, this example further illustrates the segmentation of the backlight sequence. A segment of scan points that are continuous in time and space is selected as the initial sequence. The single-line backlight data is segmented according to the time distribution of the backlight sequence in the cross-cycle ranging raw data. The segmentation principle is based on two conditions. This is combined with the basic frequency modulation step size set in Example 1. It is divided into 5 frequency modulation steps. The maximum ranging noise value between two adjacent measuring points is equal to the product of the basic frequency modulation step size and the number of frequency modulation steps set, i.e., the maximum ranging noise. Set a first threshold value, which should be slightly larger than the maximum ranging noise value. That is The first requirement for segmentation is that the difference between the ranging values ​​of two adjacent valid echo sequences is less than a first threshold. ,Right now This ensures that data from the same reverberation period are segmented into the same data sequence. The second criterion for segmentation is that the interval between two adjacent valid reverberation sequences is less than a second threshold. ,Right now Second threshold The value can be set according to parameters such as the scanning frequency and scanning speed of the lidar. When... More than one intermittent period or Then perform a cut, and then search for the next segmentation point, until all the echoes in the initial sequence are segmented.

[0027] Example 3 Building upon Examples 1-2, this example further explains the issue of reflective points that fail the continuity judgment by setting a mask with a length of not less than 5, within which the ranging sequence... The ranging difference intensity is calculated for the backlight ranging results within the mask according to different backlight periods. Specifically: ; The same method was used to calculate the ranging difference intensity for other refraction cycles. The refraction cycle corresponding to the minimum ranging difference intensity was taken as the optimal calculation result, and the ranging difference intensity must be less than a threshold. Conditions: ; threshold The value is set according to the basic frequency modulation step size. In this embodiment 3, the threshold value is... The value is equal to the basic frequency modulation step size in Example 1. ,Right now .

[0028] Example 4 This embodiment provides a fuzzy ranging reconstruction system, including... The seed light modulation module is used to control the lidar to emit pulses according to a floating stepped frequency modulation strategy; Data storage module, used to record seed light sequence and backlight sequence; The data processing module is used to perform backlight sequence segmentation, period determination, and ranging reconstruction. The data output module is used to output point cloud data containing real distance information.

[0029] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A fuzzy ranging reconstruction method, characterized in that, Includes the following steps: S1. A floating step frequency modulation strategy is used to modulate the frequency of the seed light pulse emitted by the lidar. The time interval between the emission of adjacent seed lights is randomly selected from a pre-made set, and the time modulation amount between adjacent seed lights is not equal. S2. Store the seed light sequence of the pulse emission and the back light sequence reflected by the target separately. The seed light sequence is the time difference between the current seed light and the previous seed light, and the back light sequence is the time difference between the current back light and its nearest seed light. S3. Based on the continuity of ranging and the frequency modulation step characteristics, the return light sequence is segmented and the emission period to which the return light sequence belongs is determined; S4. Based on the solved backlight period, combined with the speed of light and time difference, the distance measurement value is reconstructed.

2. The fuzzy ranging reconstruction method according to claim 1, characterized in that, In step S1, the frequency modulation amplitude of the floating step frequency modulation is The transmission time of each pulse is delayed or advanced based on the current cycle.

3. The fuzzy ranging reconstruction method according to claim 2, characterized in that, Step S1 also includes setting the basic frequency modulation step size. And several frequency modulation steps N, basic frequency modulation step size The frequency modulation amplitude of the floating stepped frequency modulation is determined by the scanning frequency of the lidar. In prefabricated sets Randomly selected from the list.

4. The fuzzy ranging reconstruction method according to claim 3, characterized in that, Basic frequency modulation step size The product of the frequency modulation step N numbers corresponds to the maximum ranging noise value between two adjacent measurement points.

5. The fuzzy ranging reconstruction method according to claim 1, characterized in that, In step S2, the seed light sequence of the pulse emission is stored, and only the seed light within the first n sweep cycles before the return light is stored. The value of n is equal to the maximum number of return light cycles supported by the lidar.

6. The fuzzy ranging reconstruction method according to claim 1, characterized in that, In step S3, the criteria for segmenting the backlight sequence are: if the difference between the ranging values ​​of two adjacent valid backlight sequences is less than the first threshold, and the number of discontinuities in these two valid backlight sequences is less than the second threshold, they are divided into the same data segment; otherwise, the segmentation operation is performed.

7. The fuzzy ranging reconstruction method according to claim 6, characterized in that, The first threshold value is set to be slightly greater than the maximum ranging noise value, while the second threshold value is set according to the scanning frequency and scanning rotation speed parameters of the lidar.

8. The fuzzy ranging reconstruction method according to claim 1, characterized in that, Step S3, determining the emission period of the return light sequence includes the following steps: Several ranging sequences under assumed reverberation periods are constructed. In the ranging sequences, it is checked whether there are at least 5 consecutive points where the absolute value of the ranging change is less than the continuity judgment threshold. The continuity judgment threshold is set according to the lidar parameters and the scanning scene. If such a sequence exists, it proves that the assumed reverberation period is correct; otherwise, it proves that the assumption is incorrect. The correct reverberation period is used as the starting period of the ranging sequence in which these points are located, and the period of the remaining points is confirmed by expanding point by point based on this.

9. The fuzzy ranging reconstruction method according to claim 8, characterized in that, For the reverberation points that fail the continuity test, a mask with a length of not less than 5 is set up. The sum of the squares of the distance differences between adjacent points under different reverberation periods is calculated as the difference intensity. The point with the smallest difference intensity that is below a set threshold is selected. The reverberation period is used as the final judgment result, and a threshold is set. The value is equal to the basic frequency modulation step size. .

10. A system for a fuzzy ranging reconstruction method according to any one of claims 1-9, characterized in that, include The seed light modulation module is used to control the lidar to emit pulses according to a floating stepped frequency modulation strategy; Data storage module, used to record seed light sequence and backlight sequence; The data processing module is used to perform backlight sequence segmentation, period determination, and ranging reconstruction. The data output module is used to output point cloud data containing real distance information.

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