Multi-obstacle positioning detection method based on ultrasonic radar

Abstract

The invention belongs to the technical field of automotive electronics, and discloses a multi-obstacle positioning detection method based on ultrasonic radars, which comprises the following steps of: S1, scheduling the work of slave ultrasonic radars through a master ultrasonic radar controller, so that the plurality of ultrasonic radars work simultaneously to detect obstacles; s2, performing obstacle distance calculation and interference filtering calculation according to echo data measured by each ultrasonic radar so as to obtain effective obstacle distance data; s3, calculating and obtaining obstacle point cloud data through a triangle algorithm; and S4, carrying out filtering calculation on the obstacle point cloud data through a clustering algorithm to obtain effective obstacle point coordinates, and filtering out invalid point coordinates. According to the method, the detection performance can be guaranteed, the response time requirement can be met, and the problems that only the nearest detection distance is processed, the polling period is long, the emergency braking requirement is not met, and the response time requirement is not met in ultrasonic radar system multi-obstacle detection are successfully solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of automobile electronics, and in particular relates to a multi-obstacle positioning and detection method based on ultrasonic radar. Background Art

[0002] At present, with the continuous development of automotive electronic technology, automobile intelligence has become a general trend. Reversing radar mainly solves the problems of scratching and collision caused by blind spots in the driver's field of vision during reversing, allowing the driver to have a clearer judgment of the obstacles around the car body. The ultrasonic radar system has gradually developed from a general warning function to a function that requires emergency braking. The general ultrasonic radar warning system only processes the nearest detection distance, and does not care about the actual location and number of obstacles. It does not meet the needs of emergency braking, and the polling cycle is long, which does not meet the response time requirements. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a multi-obstacle positioning detection method based on ultrasonic radar. The present invention aims to solve the problem that the existing reversing radar calibration technology only processes the closest detection distance, has a long polling cycle, does not meet the emergency braking requirements, and does not meet the response time requirements.

[0004] The present invention provides a multi-obstacle positioning and detection method based on ultrasonic radar, comprising the following steps:

[0005] S1. The master ultrasonic radar controller schedules the slave ultrasonic radars to work simultaneously, so that multiple ultrasonic radars can detect obstacles;

[0006] S2. Obstacle distance calculation and interference filtering calculation are performed based on the echo data obtained by each ultrasonic radar measurement, thereby obtaining effective obstacle distance data;

[0007] S3. Obstacle point cloud data is obtained by calculating the obstacle distance data in step S2 through a triangulation algorithm;

[0008] S4. Perform filtering calculation on the obstacle point cloud data through clustering algorithm to obtain the valid obstacle point coordinates and filter out the invalid point coordinates.

[0009] Furthermore, in step S1, before the ultrasonic radar senses an obstacle, it is necessary to first perform status detection, parameter setting and gain compensation on the ultrasonic radar.

[0010] Furthermore, in step S1, before scheduling each ultrasonic radar, it is necessary to load the channel number and control command of the self-transmitting and self-receiving radar that currently needs to work, and only receive the radar channel number and control command.

[0011] Further, step S2 includes the following sub-steps:

[0012] S2.1 performs obstacle distance calculation and interference filtering calculation based on the echo data measured by each ultrasonic radar, thereby obtaining the obstacle distance and echo width;

[0013] S2.2 Validity judgment of a single distance value;

[0014] The echo width corresponding to the calculated single distance value is compared with the set echo width requirement. If it meets the requirement, the single distance value is determined to be valid;

[0015] S2.3 determines whether the distance value is a valid distance by the deviation;

[0016] The deviation of the distance values ​​detected by the same ultrasonic radar for the same obstacle three times in a row is judged, and the three groups of distance values ​​that meet the deviation requirements are determined as effective distances.

[0017] Further, the content of the triangle algorithm is: based on the obstacle distance data of step S2, the effective distances of multiple obstacles detected by the self-transmitting and self-receiving ultrasonic radar are respectively calculated with the effective distances of multiple obstacles detected by the receiving ultrasonic radar, to obtain multiple obstacle coordinate points, i.e., obstacle point cloud data;

[0018] The effective distance of multiple obstacles means that in the same ranging cycle, the same ultrasonic radar can sense the distance of multiple obstacles relative to the ultrasonic radar and resolve them into an array in the same cycle; the direct echo distance values ​​and indirect echo distance values ​​of different obstacles can form a triangle, and the obstacle coordinate points are obtained through coordinate calculation, thereby obtaining the obstacle point cloud data.

[0019] Furthermore, in step S4, when the clustering algorithm is used to filter the obstacle point cloud data, the front and rear radar coordinates need to be calculated separately; when the same obstacle is stably detected, at least three coordinate points will be generated, and the number of clusters ≥ 3 is considered a valid coordinate point;

[0020] The calculation of the front and rear radar coordinates separately refers to providing the obstacle coordinate point data detected by the front and rear ultrasonic radars to the clustering algorithm model for clustering calculation.

[0021] When the same obstacle is stably detected, at least three coordinate points will be generated, which means that the same obstacle will be stably detected three times in a row within the effective detection range, so that three direct echoes and indirect echoes will form three effective coordinates. At the same time, there are four ultrasonic radar sensors on the front and back sides respectively. The same obstacle will be detected by the probes of multiple groups of ultrasonic radar sensors, thus forming more than three effective coordinate points and forming a cluster of points.

[0022] Beneficial effects:

[0023] The present invention proposes a multi-obstacle positioning detection method based on ultrasonic radar, comprising the following steps: S1. The main ultrasonic radar controller is used to schedule the work of the slave ultrasonic radar, so that multiple ultrasonic radars work simultaneously to detect obstacles; S2. The obstacle distance is calculated and interference filtering is performed through the echo data measured by each ultrasonic radar, so as to obtain effective obstacle distance data; S3. Based on the obstacle distance data of step S2, the obstacle point cloud data is calculated by the triangle algorithm; S4. The obstacle point cloud data is filtered and calculated by the clustering algorithm to obtain the effective obstacle point coordinates and filter out the invalid point coordinates. The present invention successfully solves the problem that the ultrasonic radar system multi-obstacle detection only processes the nearest detection distance, the polling cycle is long, and the emergency braking requirements and response time requirements are not met. It can not only ensure the detection performance, but also meet the response time requirements.

[0024] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a schematic flow chart of a multi-obstacle positioning and detection method based on ultrasonic radar according to the present invention;

[0026] Figure 2 This is a schematic diagram of the ultrasonic radar status detection process;

[0027] Figure 3 A schematic diagram of the ultrasonic radar control command loading process;

[0028] Figure 4 This is a schematic diagram of the triangle algorithm flow;

[0029] Figure 5 The figure is a schematic diagram of the clustering algorithm flow. DETAILED DESCRIPTION

[0030] In order to make the technical solutions, advantages and purposes of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of this application.

[0031] like Figure 1 As shown, the present invention provides a multi-obstacle positioning and detection method based on ultrasonic radar, comprising the following steps:

[0032] S1. The master ultrasonic radar controller schedules the slave ultrasonic radars to work simultaneously, so that multiple ultrasonic radars can detect obstacles;

[0033] Before the ultrasonic radar senses obstacles, it is necessary to complete the status detection and parameter configuration of the ultrasonic radar, including: detecting whether the ultrasonic radar is online and working normally; setting threshold parameters; setting gain compensation; the process of ultrasonic radar status detection is as follows: Figure 2 As shown;

[0034] Before scheduling each ultrasonic radar, it is necessary to load the channel number and control command of the currently required self-transmitting and self-receiving radar, and only receive the radar channel number and control command;

[0035] The ultrasonic radar control command loading process is as follows Figure 3 As shown, first determine the channel number of the current rear side self-transmitting and self-receiving radar sensor, and select A or B ranging command to fill in the control command according to the result of the last obstacle detection, and determine the channel number and control command of the receiving radar sensor according to the determined channel number of the rear side self-transmitting and self-receiving radar sensor. Then determine the channel number of the current front side self-transmitting and self-receiving radar sensor, and select A or B ranging command to fill in the control command according to the result of the last obstacle detection, and determine the channel number and control command of the receiving radar sensor according to the determined channel number of the front side self-transmitting and self-receiving radar sensor.

[0036] S2. Obstacle distance calculation and interference filtering calculation are performed based on the echo data obtained by each ultrasonic radar measurement, thereby obtaining effective obstacle distance data;

[0037] In this embodiment, the number of ultrasonic radars is at least 8, that is, the reversing radar includes at least 8 ultrasonic radar sensors.

[0038] S2.1 performs obstacle distance calculation and interference filtering calculation based on the echo data measured by each ultrasonic radar, thereby obtaining the obstacle distance and echo width;

[0039] S2.2 Validity judgment of a single distance value;

[0040] The echo width corresponding to the calculated single distance value is compared with the set echo width requirement. If it meets the requirement, the single distance value is determined to be valid;

[0041] The setting of effective echo width value is related to detection distance and detection range;

[0042] S2.3. Determine whether the distance value is a valid distance by the deviation;

[0043] The deviation of the distance values ​​detected by the same ultrasonic radar and the same obstacle three times in a row is judged, and the three sets of distance values ​​that meet the deviation requirements are judged as effective distances;

[0044] The deviation of the distance values ​​detected three times in a row is related to the vehicle movement loading.

[0045] S3. Based on the obstacle distance data in step S2, the obstacle point cloud data is calculated by the triangle algorithm. The triangle algorithm process is as follows: Figure 4 As shown;

[0046] The triangle algorithm calculates the obstacle coordinates by combining the effective distance detected by the self-transmitting and self-receiving ultrasonic radar with the effective distance of the ultrasonic radar that only receives the obstacle; the effective distances of multiple obstacles detected by the self-transmitting and self-receiving ultrasonic radar are respectively calculated with the effective distances of multiple obstacles detected by the ultrasonic radar that only receives the obstacle to obtain multiple obstacle coordinate points;

[0047] The effective distance of multiple obstacles means that in the same ranging cycle, the same ultrasonic radar can sense the distance of multiple obstacles relative to the ultrasonic radar and resolve them into an array in the same cycle; the direct echo distance values ​​and indirect echo distance values ​​of different obstacles can form a triangle, and coordinate calculation is required to obtain the obstacle coordinate points.

[0048] S4. The obstacle point cloud data is filtered and calculated by clustering algorithm to obtain the valid obstacle point coordinates and filter out the invalid point coordinates. The clustering algorithm process is as follows: Figure 5 As shown;

[0049] The clustering algorithm needs to separate the front and rear radar coordinates for filtering calculation of point cloud data; when the same obstacle is stably detected, at least three coordinate points will be generated, and the number of clusters must be greater than or equal to 3 to be considered a valid coordinate point;

[0050] Calculating the front and rear radar coordinates separately means giving the obstacle coordinate point data detected by the front and rear ultrasonic radars to the clustering algorithm model respectively for clustering calculation. When the same obstacle is stably detected, at least three coordinate points will be generated, which means that when the same obstacle is within the effective detection range, it will be stably detected three times in a row, so that three direct echoes and indirect echoes will form three valid coordinates. At the same time, there are four ultrasonic radar sensors on the front and rear sides. The same obstacle may be detected by multiple sets of probes, thus forming more than three valid coordinate points, forming a cluster of clustered points.

[0051] It is hereby declared that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should be included in the scope of the claims of the present invention.

Claims

1. A multi-obstacle positioning and detection method based on ultrasonic radar, characterized in that: The following steps are involved: S1. The master ultrasonic radar controller schedules the slave ultrasonic radars to work simultaneously, so that multiple ultrasonic radars can detect obstacles; S2. Obstacle distance calculation and interference filtering calculation are performed based on the echo data obtained by each ultrasonic radar measurement, thereby obtaining effective obstacle distance data; S3. Obstacle point cloud data is obtained by calculating the obstacle distance data in step S2 through a triangulation algorithm; S4. Perform filtering calculation on the obstacle point cloud data through clustering algorithm to obtain the valid obstacle point coordinates and filter out the invalid point coordinates.

2. A method for locating and detecting multiple obstacles based on ultrasonic radar according to claim 1, characterized in that: In step S1, before the ultrasonic radar senses an obstacle, it is necessary to first perform status detection, parameter setting and gain compensation on the ultrasonic radar.

3. A method for locating and detecting multiple obstacles based on ultrasonic radar according to claim 2, characterized in that: In step S1, before scheduling each ultrasonic radar, it is necessary to load the channel number and control command of the self-transmitting and self-receiving radar that needs to work currently, and only receive the radar channel number and control command.

4. A method for locating and detecting multiple obstacles based on ultrasonic radar according to claim 3, characterized in that: Step S2 includes the following sub-steps: S2.1 performs obstacle distance calculation and interference filtering calculation based on the echo data measured by each ultrasonic radar, thereby obtaining the obstacle distance and echo width; S2.2 Validity judgment of a single distance value; The echo width corresponding to the calculated single distance value is compared with the set echo width requirement. If it meets the requirement, the single distance value is determined to be valid; S2.3 determines whether the distance value is a valid distance by the deviation; The deviation of the distance values ​​detected by the same ultrasonic radar for the same obstacle three times in a row is judged, and the three groups of distance values ​​that meet the deviation requirements are determined as effective distances.

5. A method for locating and detecting multiple obstacles based on ultrasonic radar according to claim 4, characterized in that: The content of the triangle algorithm is: based on the obstacle distance data of step S2, the effective distances of multiple obstacles detected by the self-transmitting and self-receiving ultrasonic radar are respectively calculated with the effective distances of multiple obstacles detected by the receiving ultrasonic radar, to obtain multiple obstacle coordinate points, i.e., obstacle point cloud data; The effective distance of multiple obstacles means that in the same ranging cycle, the same ultrasonic radar can sense the distance of multiple obstacles relative to the ultrasonic radar and resolve them into an array in the same cycle; the direct echo distance values ​​and indirect echo distance values ​​of different obstacles can form a triangle, and the obstacle coordinate points are obtained through coordinate calculation, thereby obtaining the obstacle point cloud data.

6. A method for locating and detecting multiple obstacles based on ultrasonic radar according to claim 5, characterized in that: In step S4, when the clustering algorithm is used to filter the obstacle point cloud data, the front and rear radar coordinates need to be calculated separately; when the same obstacle is stably detected, at least three coordinate points will be generated, and the number of clusters ≥ 3 is considered a valid coordinate point; The calculation of the front and rear radar coordinates separately refers to providing the obstacle coordinate point data detected by the front and rear ultrasonic radars to the clustering algorithm model for clustering calculation. When the same obstacle is stably detected, at least three coordinate points will be generated, which means that the same obstacle will be stably detected three times in a row within the effective detection range, so that three direct echoes and indirect echoes will form three effective coordinates. At the same time, there are four ultrasonic radar sensors on the front and back sides respectively. The same obstacle will be detected by the probes of multiple groups of ultrasonic radar sensors, thus forming more than three effective coordinate points and forming a cluster of points.

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