A method for detecting obstacles behind a vehicle based on magnetic sensors

Abstract

This invention discloses a method for obstacle-behind detection based on magnetic sensors. It detects magnetic field information near targets behind obstacles such as walls using magnetic sensors, and then calculates the target's position and characteristic magnetic moment based on the obtained magnetic field information. A single magnetic sensor is used to measure the three-dimensional vector intensity of the magnetic field near targets behind obstacles such as walls; a magnetic sensor array is used to measure the magnetic gradient tensor near targets behind obstacles such as walls, thus locating the target. This invention can effectively detect targets behind metallic media. Furthermore, this invention can also effectively solve the problems of blind spots and target occlusion in traditional single-node obstacle-behind detection through network detection.

Description

Technical Field

[0001] This invention belongs to the field of sensor technology, specifically relating to a method for detecting obstacles behind objects based on a magnetic sensor. Background Technology

[0002] Obstacle detection equipment can, to a certain extent, detect life and targets behind obstacles.

[0003] Common methods for detecting obstacles behind them include optical detectors, ultrasonic detectors, and through-wall radar, among which:

[0004] 1) Optical detectors are very effective at detecting the human body, but they require a clear line of sight to the target. This means that for target detection inside buildings, the target must be in an unobstructed location, such as near a window;

[0005] 2) Although ultrasonic detectors have a certain penetration capability, they are susceptible to noise and temperature, and their propagation attenuation is severe in layered media, resulting in poor penetration.

[0006] 3) Through-wall detection radar typically penetrates obstacles by transmitting ultra-wideband signals and processes the received data to detect targets hidden behind them. However, due to the physical properties of electromagnetic waves, through-wall detection radar has very poor ability to penetrate metal and is only suitable for detecting targets behind non-metallic media, making detection in metallic environments extremely difficult.

[0007] Furthermore, research shows that novel WiFi-based passive radar can overcome the problems of high cost, high power consumption, and complex transmitter / receiver design associated with electromagnetic waves. However, its over-reliance on WiFi access points within buildings makes it unsuitable for detection in unknown environments.

[0008] Typically, obstacle-behind detection systems are deployed individually behind walls to detect targets, which has limitations. For example, targets may be missed due to weak echoes when obscured. Furthermore, the detection area of ​​a single unit is limited, resulting in blind spots. Therefore, the concept of networked through-wall detection has been proposed. This involves deploying multiple detectors on one side of a wall or on different walls of the same building. By observing the target from multiple angles and obtaining more information, the probability of false targets can be reduced, the detection probability of targets obscured or mutually obscured by objects can be increased, and data from multiple arrays can be fused to obtain more comprehensive information about the target.

[0009] Based on the above research background, traditional obstacle-behind detection methods suffer from strong obstacle obstruction, hindering effective target detection, particularly limiting their ability to detect targets behind metallic obstacles. Furthermore, traditional single obstacle-behind detectors exhibit blind spots. In contrast, networked detection using obstacle-behind detectors can effectively address these issues. Therefore, proposing novel obstacle-behind detection methods and systems, especially for identifying magnetic targets behind obstacles, is an urgent problem to be solved. Summary of the Invention

[0010] To overcome the shortcomings of existing technologies, this invention provides a method for obstacle-behind detection based on magnetic sensors. The method uses magnetic sensors to detect magnetic field information near targets behind obstacles such as walls, and then calculates the position and characteristic magnetic moment of the target based on the obtained magnetic field information. A single magnetic sensor is used to measure the three-dimensional vector intensity of the magnetic field near the target behind the obstacle, and a magnetic sensor array is used to measure the magnetic gradient tensor near the target to locate the target. This invention can effectively detect targets behind metallic media. Furthermore, this invention can also effectively solve the problems of blind spots and target occlusion in traditional single-node obstacle-behind detection through network detection.

[0011] The technical solution adopted by this invention to solve its technical problem includes the following steps:

[0012] Step 1: Place a single magnetic sensor or array of magnetic sensors behind the obstacle, with the magnetic target in front of the obstacle;

[0013] Step 2: When placing a single magnetic sensor to detect moving magnetic targets, the specific steps are as follows:

[0014] Step 2-1: Magnetic sensor measures the three components of the magnetic field;

[0015] After the magnetic sensor detects the three components of the magnetic field, it converts the magnetic field strength into an analog voltage signal proportionally, and transmits the analog voltage signal to the data acquisition card through the data cable. The data acquisition card then converts the continuous analog voltage signal into a discrete digital voltage signal.

[0016] Step 2-2: Send the digital voltage signal to the information processing terminal;

[0017] Steps 2-3: The information processing terminal recovers the digital voltage signal into a three-component magnetic field signal and processes it to determine the target's movement information;

[0018] (1) Component B of the magnetic field on the X-axis x When a magnetic target passes by, a maximum and a minimum value are generated. When the object travels back and forth, the order of the two extreme values ​​is reversed.

[0019] (2) Component B of the magnetic field on the Y-axis y With B x The trends are similar, but the directions of change are opposite.

[0020] (3) Component of the magnetic field on the Z-axis B z There are two peaks, and the positions of the two poles represent the two times the object passes through the magnetic sensor.

[0021] (4) Determine the distance l between the magnetic sensor and the target using the tangent method;

[0022] First, draw five tangent lines to the horizontal magnetic anomaly. Three of these tangent lines pass through the maximum and minimum points, respectively, while the other two pass through the two inflection points of the curve. The five lines intersect at four points with x1, x2, x3, and x4 as their x-coordinates. The distance formula is as follows:

[0023]

[0024] Step 3: When placing the magnetic sensor array, it is used for magnetic target localization, as follows:

[0025] Step 3-1: A detection system is constructed using a magnetic sensor array. One detection system includes five three-component magnetic sensors, numbered 1 to 5. The five magnetic sensors are arranged in a plane cross, and the distance between adjacent magnetic sensors is d.

[0026] Step 3-2: Obtain the magnetic gradient tensor near the target using a magnetic sensor array;

[0027] Step 3-3: Use the Zigbee module to network the magnetic sensors and send the magnetic gradient tensor obtained by each magnetic sensor to the information processing terminal.

[0028] Steps 3-4: The information processing terminal processes the magnetic gradient tensors obtained from each magnetic sensor to determine the target's position information.

[0029] 1) Calculate the gradient of the magnetic field components of the three-component magnetic sensor array;

[0030] The specific method is as follows: Magnetic sensor No. 1 measures the three-component magnetic field; magnetic sensors No. 2 and No. 3 measure the rate of change of the magnetic component in the y-direction; magnetic sensors No. 4 and No. 5 measure the rate of change of the magnetic component in the x-direction; the specific quantities measured are shown in equation (2):

[0031]

[0032] Where d is the baseline distance between adjacent magnetic sensors, and H mnm = x, y, z; n = 1, 2, 3, 4, 5 represent the three components H of the magnetic field vector measured by the nth sensor. m The value of is obtained, and the resulting magnetic gradient tensor is shown in equation (3):

[0033]

[0034] 2) Magnetic target localization based on magnetic gradient tensor;

[0035] When locating a magnetic target, the distance r from the magnetic target to the magnetic sensor array is obtained based on the calculated magnetic gradient tensor. The specific calculation method is shown in equation (4):

[0036]

[0037] Among them, H x H y H z The three-component magnetic field values ​​measured by magnetic sensor No. 1;

[0038] After the location of the magnetic target is determined, the magnetic moment of the magnetic target is determined according to equation (5):

[0039]

[0040] Preferably, the magnetic sensor array is a fluxgate sensor or an optical pump sensor.

[0041] The beneficial effects of this invention are as follows:

[0042] Using this invention, targets behind metallic media can be detected very effectively. Furthermore, this invention, through a detection network, effectively solves the problems of blind spots and target occlusion inherent in traditional single-node obstacle detection. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the operation of a single detection system for the obstacle rear detection method based on magnetic sensors of the present invention.

[0044] Figure 2 This is a flowchart illustrating the workflow of a single detection system for the obstacle rear detection method based on magnetic sensors according to the present invention.

[0045] Figure 3 The image shows the waveforms of the three components of the magnetic field measured by a single detection system in the obstacle rear detection method based on magnetic sensors of this invention.

[0046] Figure 4 This is a schematic diagram of the magnetic anomaly tangent method of the present invention.

[0047] Figure 5This is a schematic diagram of the network detection system of the obstacle rear detection method based on magnetic sensors of the present invention.

[0048] Figure 6 This is a flowchart illustrating the workflow of the network detection system for the obstacle rear detection method based on magnetic sensors of the present invention. Detailed Implementation

[0049] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0050] The purpose of this invention is to provide a method for detecting targets behind obstacles based on magnetic sensors, aiming to provide a new method for detecting targets behind obstacles, especially to solve the problem of detection through metal media, as well as the problem of detecting and identifying magnetic targets behind obstacles.

[0051] This invention uses a magnetic sensor to detect magnetic field information near a target behind an obstacle such as a wall; and calculates the position, characteristic magnetic moment, and other information of the target behind the obstacle based on the obtained magnetic field information.

[0052] (1) Single magnetic sensor: used to measure the three-dimensional vector intensity of the magnetic field near the target behind obstacles such as walls;

[0053] Information processing terminal: The three-dimensional vector intensity of the magnetic field is sent to the information processing terminal, which processes the three-dimensional vector intensity information of the magnetic field to determine the target's speed and direction of motion;

[0054] (2) Magnetic sensor array: used to measure the magnetic gradient tensor near the target behind obstacles such as walls;

[0055] Wireless transmission module: used to send the magnetic gradient tensor information to the information processing terminal through the wireless transmission module, and to form a detection network of multiple obstacle rear detection systems based on magnetic sensors, effectively solving problems such as detection blind spots and target occlusion;

[0056] Information processing terminal: Calculates the three-dimensional coordinate information of the magnetic target based on the magnetic gradient tensor information, and determines the position, motion, and magnetic moment information of the magnetic target.

[0057] A method for detecting obstacles behind objects based on a magnetic sensor includes the following steps:

[0058] Step 1: Place a single magnetic sensor or array of magnetic sensors behind the obstacle, with the magnetic target in front of the obstacle; the magnetic sensor array is a fluxgate sensor or an optical pump sensor.

[0059] Step 2: When placing a single magnetic sensor to detect moving magnetic targets, the specific steps are as follows:

[0060] Step 2-1: Magnetic sensor measures the three components of the magnetic field;

[0061] After the magnetic sensor detects the three components of the magnetic field, it converts the magnetic field strength into an analog voltage signal proportionally, and transmits the analog voltage signal to the data acquisition card through the data cable. The data acquisition card then converts the continuous analog voltage signal into a discrete digital voltage signal.

[0062] Step 2-2: Send the digital voltage signal to the information processing terminal;

[0063] Steps 2-3: The information processing terminal recovers the digital voltage signal into a three-component magnetic field signal and processes it to determine the target's movement information;

[0064] (1) Component B of the magnetic field on the X-axis x When a magnetic target passes by, a maximum and a minimum value are generated. When the object travels back and forth, the order of the two extreme values ​​is reversed.

[0065] (2) Component B of the magnetic field on the Y-axis y With B x The trends are similar, but the directions of change are opposite.

[0066] (3) Component of the magnetic field on the Z-axis B z There are two peaks, and the positions of the two poles represent the two times the object passes through the magnetic sensor.

[0067] (4) Determine the distance l between the magnetic sensor and the target using the tangent method;

[0068] First, draw five tangent lines to the horizontal magnetic anomaly. Three of these tangent lines pass through the maximum and minimum points, respectively, while the other two pass through the two inflection points of the curve. The five lines intersect at four points with x1, x2, x3, and x4 as their x-coordinates. The distance formula is as follows:

[0069]

[0070] Step 3: When placing the magnetic sensor array, it is used for magnetic target localization, as follows:

[0071] Step 3-1: A detection system is constructed using a magnetic sensor array. One detection system includes five three-component magnetic sensors, numbered 1 to 5. The five magnetic sensors are arranged in a plane cross, and the distance between adjacent magnetic sensors is d.

[0072] Step 3-2: Obtain the magnetic gradient tensor near the target using a magnetic sensor array;

[0073] Step 3-3: Use the Zigbee module to network the magnetic sensors and send the magnetic gradient tensor obtained by each magnetic sensor to the information processing terminal.

[0074] Steps 3-4: The information processing terminal processes the magnetic gradient tensors obtained from each magnetic sensor to determine the target's position information.

[0075] 1) Calculate the gradient of the magnetic field components of the three-component magnetic sensor array;

[0076] The specific method is as follows: Magnetic sensor No. 1 measures the three-component magnetic field; magnetic sensors No. 2 and No. 3 measure the rate of change of the magnetic component in the y-direction; magnetic sensors No. 4 and No. 5 measure the rate of change of the magnetic component in the x-direction; the specific quantities measured are shown in equation (2):

[0077]

[0078] Where d is the baseline distance between adjacent magnetic sensors, and H mn m = x, y, z; n = 1, 2, 3, 4, 5 represent the three components H of the magnetic field vector measured by the nth sensor. m The value of is obtained, and the resulting magnetic gradient tensor is shown in equation (3):

[0079]

[0080] 2) Magnetic target localization based on magnetic gradient tensor;

[0081] When locating a magnetic target, the distance r from the magnetic target to the magnetic sensor array is obtained based on the calculated magnetic gradient tensor. The specific calculation method is shown in equation (4):

[0082]

[0083] Among them, H x H y H z The three-component magnetic field values ​​measured by magnetic sensor No. 1;

[0084] After the location of the magnetic target is determined, the magnetic moment of the magnetic target is determined according to equation (5):

[0085] Specific implementation examples:

[0087] 1. Example of a single-unit detection system for obstacle rear detection based on magnetic sensors

[0088] According to the obstacle rear detection method based on magnetic sensors of the present invention, an embodiment of a single detection system based on the obstacle rear detection method based on magnetic sensors is provided, such as... Figure 1 As shown. Figure 2 This is a flowchart illustrating the workflow of a single detection system for the obstacle rear detection method based on magnetic sensors provided in this embodiment. Figure 2 As shown, the operation of a single detection system according to the obstacle rear detection method based on magnetic sensors in this embodiment specifically includes:

[0089] S1. Magnetic sensor based on fluxgate sensor measures the three components of magnetic field;

[0090] S2. Send the obtained three components of the magnetic field to the information processing terminal.

[0091] S3. The information processing terminal processes the measured three components of the magnetic field to determine the target information.

[0092] The fluxgate sensor is used to collect magnetic field information. After detecting the magnetic field, the fluxgate sensor converts the magnetic field strength into a voltage amplitude proportionally and transmits the data to a data acquisition card via a data cable. The data acquisition card converts the continuous analog voltage signal into a discrete digital voltage signal for analysis by data processing software. This embodiment uses a high-capacity battery to power the entire system, making the entire detection system a portable device.

[0093] Figure 3 The image shows the waveforms of three magnetic field components measured when a magnetic sensor based on a fluxgate sensor is positioned in front of a 10cm thick, 3m x 3m metal obstacle. A handheld magnetic target (in this example, a small screwdriver, 8cm long and 0.5cm in diameter) is passed back and forth along a 1m vertical distance behind the obstacle. The waveform characteristics are as follows:

[0094] (1) Component B of the magnetic field on the X-axis x There are two distinct fluctuations, representing one round trip. Each time the magnetic target passes by, a maximum and a minimum value are generated, and the order of the two extreme values ​​is reversed when the object travels back and forth.

[0095] (2) Component B of the magnetic field on the Y-axis y With B x The trends are similar, but the directions of change are opposite.

[0096] (3) Component of the magnetic field on the Z-axis B z There are two peaks, and the positions of the two poles represent the two times the object passed the detector.

[0097] The distance to a target can be determined using the tangent method, an empirical approach where the distance is defined as the distance between the field source and the center of the probe. When calculating the target distance, five tangents are first drawn on the horizontal magnetic anomaly. Three of these tangents pass through the maximum and minimum points, respectively, while the other two pass through the two inflection points of the curve. The five lines intersect at four points, with their abscissas being x1, x2, x3, and x4. Figure 4 As shown, the distance formula is:

[0098]

[0099] The magnetic anomaly generated by the target's motion exhibits a sinusoidal and cosine-like variation in its horizontal component. While the amplitude of this component is roughly the same for different velocities *v*, the waveform width of the resulting magnetic anomaly component varies significantly. Lower speeds result in a wider waveform width, while higher speeds produce a narrower waveform width. The velocity of the moving target can be identified based on the width of the waveform.

[0100] A single detection system based on magnetic sensors for obstacle rear detection can detect targets passing through metal media during operation. It is suitable for detecting moving vehicles, including but not limited to magnetic weapons and unmanned vehicles.

[0101] 2. Example of a network detection system for obstacle rear detection based on magnetic sensors

[0102] Because the gradient caused by magnetic anomalies is much larger than the gradient of the background magnetic field, the magnetic gradient tensor measurement is less affected by the geomagnetic field and can more clearly reflect minute changes in the magnetic field. Therefore, a fluxgate array system is used to measure the full tensor magnetic gradient. Compared to Example 1, this invention also provides an example of a network detection system:

[0103] Using Zigbee modules to network the nodes can effectively solve problems such as blind spots and target occlusion behind obstacles that exist in traditional single-node systems. At the same time, the device has a simple structure and is easy to operate.

[0104] According to the obstacle rear detection method based on magnetic sensors of the present invention, a new network detection system embodiment of the obstacle rear detection method based on magnetic sensors is provided, such as... Figure 5 As shown, a detection system includes five three-component fluxgate sensors, numbered 1-5 respectively. The five magnetic sensors are arranged in a planar cross, and the distance between adjacent magnetic sensors is d. Figure 6 This is a flowchart illustrating the workflow of the network detection system for the obstacle rear detection method based on magnetic sensors provided in this embodiment. Figure 6 As shown, the operation of the obstacle rear detection system based on a magnetic sensor according to this embodiment specifically includes:

[0105] S1. Use a fluxgate sensor array to obtain the magnetic gradient tensor near the target;

[0106] S2. Use the Zigbee module to network each measurement node and send the magnetic gradient tensor obtained by each node to the information processing terminal.

[0107] S3. The information processing terminal processes the magnetic gradient tensor obtained from each node to determine the target information.

[0108] S3 specifically includes:

[0109] 1) Calculate the gradient of the magnetic field components of the three-component magnetic sensor array.

[0110] The specific method is as follows: Fluxgate sensor No. 1 measures the three components of the magnetic field; Fluxgate sensors No. 2 and 3 measure the rate of change of the magnetic component in the y-direction; Fluxgate sensors No. 4 and 5 measure the rate of change of the magnetic component in the x-direction. The measured quantities are shown in Formula 2.

[0111]

[0112] Where d is the baseline distance between adjacent fluxgate sensors, and H mn (m = x, y, z; n = 1, 2, 3, 4, 5) represents the three components H of the magnetic field vector measured by sensor n. m The numerical value of the magnetic gradient tensor is obtained from this, as shown in Equation 3:

[0113]

[0114] 2) Magnetic target localization based on magnetic gradient tensor

[0115] For locating magnetic targets, specifically magnetic dipole R, the distance to the target is obtained based on the calculated magnetic gradient tensor. The specific calculation method is shown in Formula 4.

[0116]

[0117] Among them, H x H y H z These are the three-component magnetic field values ​​measured by fluxgate sensor No. 1. After determining the position of the magnetic target, the magnetic moment of the magnetic target can be determined according to formula 5:

[0118]

[0119] A networked detection system based on magnetic sensors for obstacle detection behind objects can detect targets through metallic media and obtain their three-dimensional coordinates. By using Zigbee modules to network the nodes, it effectively solves problems such as blind spots and target occlusion that exist in traditional single-node systems behind obstacles.

[0120] The networked detection system based on magnetic sensors for obstacle rear detection is suitable for detecting moving vehicles, including but not limited to magnetic weapons and unmanned vehicles.

[0121] This invention proposes a method for detecting obstacles behind walls based on magnetic sensors. When using this method for wall detection, it can penetrate metal media and has no significant requirements on wall thickness. It can obtain positioning results in real time, solving the problems of current electromagnetic wave or infrared detection systems that cannot penetrate metal media or thick walls. Furthermore, by forming a detection network, it can effectively solve the problems of blind spots and target occlusion in traditional single-node obstacle detection.

Claims

1. A method for detecting obstacles behind objects based on a magnetic sensor, characterized in that, Includes the following steps: Step 1: Place a single magnetic sensor or array of magnetic sensors behind the obstacle, with the magnetic target in front of the obstacle; Step 2: When placing a single magnetic sensor to detect moving magnetic targets, the specific steps are as follows: Step 2-1: Magnetic sensor measures the three components of the magnetic field; After the magnetic sensor detects the three components of the magnetic field, it converts the magnetic field strength into an analog voltage signal proportionally, and transmits the analog voltage signal to the data acquisition card through the data line. The data acquisition card then converts the continuous analog voltage signal into a discrete digital voltage signal. Step 2-2: Send the digital voltage signal to the information processing terminal; Steps 2-3: The information processing terminal recovers the digital voltage signal into a three-component magnetic field signal and processes it to determine the target's movement information; (1) Component B of the magnetic field on the X-axis x When a magnetic target passes by, a maximum and a minimum value are generated. When the object travels back and forth, the order of the two extreme values ​​is reversed. (2) Component B of the magnetic field on the Y-axis y With B x The trends are similar, but the directions of change are opposite. (3) Component of the magnetic field on the Z-axis B z There are two peaks, and the positions of the two poles represent the two times the object passes through the magnetic sensor. (4) Determine the distance l between the magnetic sensor and the target using the tangent method; First, draw five tangent lines to the horizontal magnetic anomaly. Three of these horizontal tangent lines pass through the maximum and minimum points, respectively, while the other two pass through the two inflection points of the curve. The five lines intersect at four points with x1, x2, x3, and x4 as their x-coordinates. The distance formula is as follows: Step 3: When placing the magnetic sensor array, it is used for magnetic target localization, as follows: Step 3-1: A detection system is constructed using a magnetic sensor array. One detection system includes five three-component magnetic sensors, numbered 1 to 5. The five magnetic sensors are arranged in a plane cross, and the distance between adjacent magnetic sensors is d. Step 3-2: Obtain the magnetic gradient tensor near the target using a magnetic sensor array; Step 3-3: Use the Zigbee module to network the magnetic sensors and send the magnetic gradient tensor obtained by each magnetic sensor to the information processing terminal. Steps 3-4: The information processing terminal processes the magnetic gradient tensors obtained from each magnetic sensor to determine the target's position information. 1) Calculate the gradient of the magnetic field components of the three-component magnetic sensor array; The specific method is as follows: Magnetic sensor No. 1 measures the three-component magnetic field; magnetic sensors No. 2 and No. 3 measure the rate of change of the magnetic component in the y-direction; magnetic sensors No. 4 and No. 5 measure the rate of change of the magnetic component in the x-direction; the specific quantities measured are shown in equation (2): Where d is the baseline distance between adjacent magnetic sensors, and H mn m = x, y, z; n = 1, 2, 3, 4, 5 represent the three components H of the magnetic field vector measured by the nth sensor. m The value of is obtained, and the resulting magnetic gradient tensor is shown in equation (3): 2) Magnetic target localization based on magnetic gradient tensor; When locating a magnetic target, the distance r from the magnetic target to the magnetic sensor array is obtained based on the calculated magnetic gradient tensor. The specific calculation method is shown in equation (4): Among them, H x H y H z The three-component magnetic field values ​​measured by magnetic sensor No. 1; After the location of the magnetic target is determined, the magnetic moment of the magnetic target is determined according to equation (5):

2. The obstacle rear detection method based on a magnetic sensor according to claim 1, characterized in that, The magnetic sensor array is a fluxgate sensor or an optical pump sensor.

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