An AC magnetic positioning method and system based on rotating permanent magnets

Abstract

This invention discloses an AC magnetic positioning method and system based on a rotating permanent magnet. The method includes: acquiring an AC magnetic signal; processing the AC magnetic signal to acquire its frequency and phase information; calculating the phase difference between different sensors based on the phase information; acquiring the azimuth angle of a target object based on the relationship between the phase difference and the actual azimuth angle; and retrieving the position of the target object based on its azimuth angle and frequency information to obtain its position information. This invention utilizes environmental magnetic field characteristics and a rotating permanent magnet as the source of the AC magnetic signal to achieve precise positioning, and is applicable to scenarios where other positioning technologies fail or have insufficient accuracy.

Description

Technical Field

[0001] This invention belongs to the field of magnetic positioning technology, and particularly relates to an AC magnetic positioning method and system based on a rotating permanent magnet. Background Technology

[0002] Currently, traditional positioning technologies mainly rely on GPS, inertial navigation systems (INS), and visual sensors. However, in certain scenarios (such as indoors, underground, or environments with strong electromagnetic interference), these technologies may fail or lack accuracy. GPS relies on satellite signals, which are easily obstructed by physical barriers and electromagnetic interference during propagation. Its design was originally intended for positioning in open environments and did not consider applicability in complex environments. INS is a relative positioning technology, lacking an absolute position reference, which easily leads to error accumulation problems. Furthermore, the manufacturing process of high-precision inertial sensors is complex, making cost reduction difficult. Visual positioning technology relies on visible features in the environment, but these features may be unstable or unavailable in different environments. Visual positioning performs poorly in environments with sparse features (such as solid-color walls, dark environments, and narrow pipes). Environmental factors such as changes in lighting, fog, rain, and snow also reduce the accuracy and reliability of visual positioning. Moreover, real-time image processing and feature matching require significant computational resources, placing high demands on hardware. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes an AC magnetic positioning method and system based on a rotating permanent magnet. This invention utilizes the characteristics of the ambient magnetic field and the rotating permanent magnet as the source of AC magnetic signals to achieve accurate positioning, and is applicable to scenarios where other positioning technologies fail or have insufficient accuracy.

[0004] To achieve the above objectives, the present invention provides an AC magnetic positioning method based on a rotating permanent magnet, comprising:

[0005] Acquire AC magnetic signals;

[0006] The alternating magnetic signal is processed to obtain its frequency and phase information.

[0007] Based on the phase information, the phase difference between different sensors is calculated;

[0008] Based on the relationship between the phase difference and the actual azimuth angle, the azimuth angle of the target object is obtained;

[0009] The position of the target object is inverted based on its azimuth and frequency information to obtain its position information.

[0010] Optionally, acquiring the AC magnetic signal includes: constructing a magnetic sensor array and using the magnetic sensor array to acquire the AC magnetic signal.

[0011] Optionally, processing the alternating magnetic signal to obtain its frequency and phase information includes:

[0012] The AC magnetic signal is filtered, and the filtered AC magnetic signal is subjected to a fast Fourier transform to obtain the frequency and phase information of the AC magnetic signal.

[0013] Optional, such as Figure 1 As shown, the relationship between the phase difference and the actual azimuth angle is as follows:

[0014] Δφ=k·θ

[0015] Where Δφ is the phase difference, k is the proportionality constant, and θ is the actual azimuth angle.

[0016] Optionally, the position of the target object is inverted based on its azimuth and frequency information to obtain position information, including:

[0017] Based on the azimuth and frequency information of the target object, the position of the target object is inverted using a magnetic field propagation model to obtain position information.

[0018] The present invention also discloses an AC magnetic positioning system based on a rotating permanent magnet, comprising: a data acquisition module, a data processing module, and a storage module;

[0019] The data acquisition module is used to acquire AC magnetic signals;

[0020] The data processing module is used to process the AC magnetic signal to obtain the frequency and phase information of the AC magnetic signal; calculate the phase difference between different sensors based on the phase information; obtain the azimuth angle of the target object based on the relationship between the phase difference and the actual azimuth angle; and invert the position of the target object based on the azimuth angle and frequency information of the target object to obtain position information.

[0021] The storage module is used to store location information.

[0022] Compared with the prior art, the present invention has the following advantages and technical effects:

[0023] This invention has important applications in indoor navigation and low-altitude economics, such as drone collision avoidance, underground navigation, and precise positioning in complex environments. This invention utilizes environmental magnetic field characteristics and a rotating permanent magnet as the source of AC magnetic signals to achieve precise positioning, making it suitable for scenarios where other positioning technologies fail or lack sufficient accuracy. This technology boasts advantages such as non-invasiveness, high precision, low power consumption, and strong adaptability, and has broad application prospects. Attached Figure Description

[0024] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0025] Figure 1 This is a flowchart of an AC magnetic positioning method based on a rotating permanent magnet according to an embodiment of the present invention;

[0026] Figure 2 This is a schematic diagram of the construction environment magnetic map in an embodiment of the present invention. Detailed Implementation

[0027] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0028] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0029] This embodiment proposes an AC magnetic positioning method based on a rotating permanent magnet, such as... Figure 1 As shown, the specific steps include:

[0030] Acquire AC magnetic signals;

[0031] The alternating magnetic signal is processed to obtain its frequency and phase information.

[0032] Based on the phase information, the phase difference between different sensors is calculated;

[0033] Based on the relationship between the phase difference and the actual azimuth angle, the azimuth angle of the target object is obtained;

[0034] The position of the target object is inverted based on its azimuth and frequency information to obtain its position information.

[0035] Furthermore, acquiring the AC magnetic signal includes: constructing a magnetic sensor array and using the magnetic sensor array to acquire the AC magnetic signal.

[0036] Specifically, deploying AC magnetic sources: Compared with DC magnetic sources, AC magnetic sources have stronger anti-interference capabilities, higher signal processing flexibility and dynamic response capabilities, and can achieve multi-target positioning through frequency coding.

[0037] Array setup: Rotating permanent magnet array: Several N52 cylindrical magnets with a diameter of 6mm and a length of 100mm, driven by a 0.2° stepper closed-loop motor with different mechanical speeds of 30-200Hz; TMR array: 4×4 grid with a spacing of 100cm, each node contains a triaxial TMR + 24-bit ADC + temperature-compensated crystal oscillator; Edge computing node: ARMM7 MCU + FPGA coprocessor, running 128-point FFT and 100-particle UKF.

[0038] Further, processing the alternating magnetic signal to obtain its frequency and phase information includes:

[0039] The AC magnetic signal is filtered, and the filtered AC magnetic signal is subjected to a fast Fourier transform to obtain the frequency and phase information of the AC magnetic signal.

[0040] Specifically, a TMR sensor is used to detect changes in dynamic magnetic fields, and the direction of the magnetic moment is determined by measuring changes in resistance, thereby achieving the advantages of high sensitivity, low power consumption and fast response.

[0041] Signal Acquisition and Processing: This technology acquires magnetic field signals through a magnetic sensor array, separating the amplitude and phase information of the AC signal. The specific steps are as follows: Signal Preprocessing: The acquired magnetic field signal is filtered to remove noise interference. An FFT is performed on the filtered signal to extract the frequency components and phase information. A permanent magnet rotating at a programmable mechanical speed generates an alternating low-frequency magnetic field in space. The unique frequency point f0 of this magnetic field is sampled by the TMR array and precisely extracted as a complex quantity B(f0) = |B|·e^(jφ) through a 128-point FFT. Here, |B| directly corresponds to the near-field amplitude of the magnetic dipole, which decays with distance r according to the law of 1 / r³. Therefore, the amplitude channel is used for cubic inverse distance inversion, while the phase φ of the same complex quantity records the propagation delay between the magnetic source and the sensor. The phase difference Δφ between multiple sensors and the azimuth angle θ satisfy a linear relationship of Δφ = k·θ, thus solving the azimuth angle in one step. Simultaneously, the TMR front end outputs a signal related to the magnetic field strength... The low-frequency envelope curve, proportional to the degree, is transformed into a traditional RSSI (Received Signal Strength Indicator) after low-pass filtering and detection. This RSSI forms a consistency check with |B(f0)| obtained by FFT. Penalized weighting is performed according to w_i=w_b·(RSSI / |B|)². Subsequent particle filtering or UKF fusion algorithms only need to use [|B(f0)|,φ(f0),RSSI] as the three-dimensional observation vector to complete real-time iteration without relying on the original high-dimensional sampling data, significantly reducing the MCU's computational load. Phase difference calculation: The phase difference between different sensors is calculated. Azimuth angle calculation: Based on the relationship between phase difference and azimuth angle measured in an ideal environment, the azimuth angle of the target object is calculated. Finally, the entire positioning system transforms the complex three-dimensional magnetic field problem into a linear-nonlinear hybrid estimation problem of single-frequency complex amplitude + RSSI threshold through three steps of "purification-dimensionality reduction-fusion".

[0042] Furthermore, the position of the target object is inverted based on its azimuth and frequency information to obtain position information, including:

[0043] Based on the azimuth and frequency information of the target object, the position of the target object is inverted using a magnetic field propagation model to obtain position information.

[0044] Specifically, position inversion: Phase information is directly related to the rotation angle of the permanent magnet. By using sensors to acquire the signal phase difference, the physical azimuth angle of the AC magnetic source beacon can be obtained. Combined with the dipole magnetic field 1 / r³ law attenuation propagation model, the target position is inverted, compensating for changes in the environmental magnetic field and sensor drift in real time, minimizing errors. Positioning principle: Since the magnetic field signal of the rotating permanent magnet has a clear directionality, the phase difference between sensors is directly related to the azimuth angle of the target object. Assuming the target object is located in a certain direction of the sensor array, with an azimuth angle of θ, the relationship between the phase difference Δϕ and the azimuth angle θ can be expressed as: Δφ = k·θ. Where k is a proportionality constant, depending on the distance between the sensors and the rotation frequency of the permanent magnet. By measuring the phase difference Δϕ, the azimuth angle θ of the target object can be calculated. By measuring the signal amplitude and RSSI value at the single frequency f0 of the FFT, the distance, magnetic moment, and other information are inverted using the dipole magnetic field 1 / r³ law attenuation propagation model. Through particle filtering algorithm, multiple iterations, and minimization of errors, high-precision magnetic positioning is achieved.

[0045] This embodiment also provides an AC magnetic positioning system based on a rotating permanent magnet, including:

[0046] TMR magnetic sensor array: used to pre-build a magnetic field map of the environment and measure magnetic field signals in real time.

[0047] Data processing unit: processes sensor data in real time and constructs a magnetic field map by combining weighted RSSI and particle filter algorithms. Figure 2 ), and the inversion target location.

[0048] Storage unit: Stores magnetic field maps and sensor data.

[0049] High-precision motor: provides a stable AC magnetic signal.

[0050] This embodiment uses "mechanical rotation + permanent magnet" to construct a low-frequency AC magnetic dipole, avoiding the defects of traditional coil-type AC magnetic sources such as high power consumption, easy saturation, and waveform distortion.

[0051] The orthogonal components of the alternating magnetic field are captured using a TMR magnetic sensor array. The azimuth angle is extracted in one step using the "phase difference → azimuth angle" model, and the distance is inverted using the "amplitude-cubic inverse ratio-dipole model".

[0052] After completing the distance and azimuth measurement inversion, a joint weighting function of "distance-azimuth" is introduced: w_mi=1 / (n*(d_i+ε)) or w_i=1 / n*(d_i^k), k=3~4; w_ai=1 / n-w_mi. A real-time environmental magnetic field compensation term, an online calibration term based on sensor zero-point drift, and a dynamic weighting term based on SNR are embedded within this objective function, thereby transforming the static map dependence of traditional magnetic positioning into a dynamic closed loop of "real-time phase calculation + amplitude iterative inversion".

[0053] The following is a detailed description of this embodiment:

[0054] Without using public Wi-Fi, turning off UWB base stations for energy saving, and without using visual features or GPS positioning, the robot is required to complete the inspection of floor equipment with a positioning error of ≤0.1m.

[0055] System deployment:

[0056] a. AC magnetic beacon (fixed end):

[0057] One rotating permanent magnet beacon is installed every 3 meters on each floor:

[0058] N52 cylindrical motor, Φ6mm×100mm; brushless motor, 24V DC power supply.

[0059] The mechanical speed is 60-200Hz (corresponding to the AC magnetic field frequency f0=60Hz, which is different from the ambient 50Hz power frequency).

[0060] b. Mobile robot:

[0061] Bottom 4×4 TMR array (16 nodes, 10cm spacing), triaxial sensitivity 50nT√Hz;

[0062] Edge computing: STM32H7 main frequency 480MHz + FPGA 128-point FFT, average power consumption 220mW;

[0063] The wheel encoder + MEMSIMU is only used for coarse trajectory estimation and does not depend on its absolute accuracy.

[0064] Step-1 Signal Acquisition:

[0065] The robot enters the elevator lobby on a certain floor → the TMR array samples for 0.5s and obtains 16 channels of 60Hz complex amplitude B_i=|B_i|·e^(jφ_i).

[0066] Step-2 Phase difference → Azimuth angle:

[0067] Select reference sensor S0 (array geometric center) and calculate Δφ_i = φ_i − φ_0;

[0068] Based on the calibration curve Δφ=1.22·θ (θ is the relative beacon azimuth angle, in rad), calculate 16 θ_i;

[0069] After RANSAC removed two outliers, the average azimuth angle σ_θ = 0.05 rad (≈ 2.9°).

[0070] Step-3 Amplitude → Distance:

[0071] Take the median of |B| and invert the distance r according to the dipole 1 / r³ model, with the formula r=(μ0m / 4π|B|)^(1 / 3), where the magnetic moment m has been calibrated during installation (m=0.74-0.81A·m²).

[0072] Step-4 Single-point positioning:

[0073] Given the beacon map coordinates P_beacon=(x_b,y_b), and combining this with (r,θ), we can obtain the robot's horizontal coordinates:

[0074] x=x_b+r·cosθ, y=y_b+r·sinθ.

[0075] Step-5 Error Closure:

[0076] The robot continued to move 3m and captured the same beacon again. The difference between the two positioning was 0.07m, which meets the requirement of <0.1m.

[0077] Key measured data:

[0078] Beacon coverage radius: <0.15m error within 0.5–4m; <0.30m within 4–6m; >6m triggers handover to adjacent beacons.

[0079] Interference suppression: The UPS power distribution room operates at a 50Hz power frequency of 22µT, while this system operates at 60Hz with an out-of-band suppression of 42dB, requiring no additional shielding.

[0080] Battery life: The robot is powered by six 21700 lithium batteries (24V / 20Ah each). The magnetic positioning module consumes only 0.22W, and the entire machine consumes 8W, allowing it to work continuously for 4.5 hours.

[0081] Deployment time: 16 beacons per floor, 2 engineers completed installation and calibration in 50 minutes; no mechanical structure modification is required on the robot, it is plug and play.

[0082] Emergency Scenario Verification:

[0083] A simulated fire alarm cut off power to the entire building, with the UPS supplying power only to emergency lighting and magnetic beacons. Magnetic positioning was effective in 96% of cases.

[0084] In complex indoor environments where Wi-Fi is off, visual obstruction is present, and UWB energy saving is ineffective, the rotating permanent magnet AC magnetic positioning system achieves reliable navigation at the floor-to-room level with an accuracy of <0.1m and a power consumption of <1W. It provides a supplementary indoor positioning method for building inspection and emergency disaster relief that requires no wiring, no spectrum application, and is ready to use immediately.

[0085] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of AC magnetic positioning based on rotating permanent magnets, characterized in that, include: Acquire AC magnetic signals; The alternating magnetic signal is processed to obtain its frequency and phase information. Based on the phase information, the phase difference between different sensors is calculated; Based on the spatial relationship between the phase difference and the actual azimuth angle, the azimuth angle of the target object is obtained; When the alternating magnetic field is a low-frequency alternating magnetic field, the relationship between the phase difference and the actual azimuth angle is as follows: Δφ=k·θ Where Δφ is the phase difference, k is the proportionality constant, and θ is the actual azimuth angle; The position of the target object is inverted based on its azimuth and frequency information to obtain its position information.

2. The AC magnetic positioning method based on a rotating permanent magnet according to claim 1, characterized in that, Acquiring AC magnetic signals includes: constructing a magnetic sensor array and using the magnetic sensor array to collect the AC magnetic signals.

3. The AC magnetic positioning method based on a rotating permanent magnet according to claim 1, characterized in that, Processing the AC magnetic signal to obtain its frequency and phase information includes: The AC magnetic signal is filtered, and the filtered AC magnetic signal is subjected to a fast Fourier transform to obtain the frequency and phase information of the AC magnetic signal.

4. The AC magnetic positioning method based on a rotating permanent magnet according to claim 1, characterized in that, The position of the target object is inverted based on its azimuth and frequency information to obtain position information including: Different magnetic beacons can be identified based on the azimuth and frequency information of the target object; Based on the magnetic beacon, the position of the target object is inverted by combining the magnetic field propagation model and the inverse cubic attenuation of amplitude to obtain position information.

5. An AC magnetic positioning system based on a rotating permanent magnet, implemented according to any one of claims 1-4, characterized in that, include: Data acquisition module, data processing module, and storage module; The data acquisition module is used to acquire AC magnetic signals; The data processing module is used to process the AC magnetic signal to obtain the frequency and phase information of the AC magnetic signal; and to calculate the phase difference between different sensors based on the phase information. Based on the relationship between the phase difference and the actual azimuth angle, the azimuth angle of the target object is obtained; The position of the target object is inverted based on the azimuth and frequency information of the target object to obtain position information; The storage module is used to store location information.

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