CN114046785A - Magnetic detection signal linear noise filtering method and system, computer readable storage medium, magnetic navigation sensor and AGV trolley - Google Patents

Magnetic detection signal linear noise filtering method and system, computer readable storage medium, magnetic navigation sensor and AGV trolley Download PDF

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Publication number
CN114046785A
CN114046785A CN202111325177.5A CN202111325177A CN114046785A CN 114046785 A CN114046785 A CN 114046785A CN 202111325177 A CN202111325177 A CN 202111325177A CN 114046785 A CN114046785 A CN 114046785A
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China
Prior art keywords
magnetic
detection signal
linear noise
magnetic detection
moment
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CN202111325177.5A
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Chinese (zh)
Inventor
吴建得
彭润欣
叶海洋
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Guangdong Weidian Technology Co ltd
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Guangdong Weidian Technology Co ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20Instruments for performing navigational calculations
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0259Control of position or course in two dimensions specially adapted to land vehicles using magnetic or electromagnetic means

Abstract

A magnetic detection signal linear noise filtering method and system, a computer readable storage medium, a magnetic navigation sensor and an AGV relate to the technical field of AGV magnetic navigation. The filtering method comprises the following steps: step 1: let Yi=Xi‑1(ii) a Step 2: calculating Si=Pi‑1+ Q; and step 3: calculating Ki=Si*(Si+R)‑1(ii) a And 4, step 4: calculating Xi=Yi+Ki*(Zi‑Yi) (ii) a And 5: calculating Pi=(1‑Ki)*Si(ii) a i is the serial number of the moment of the input digital signal; y isiThe predicted value at the ith moment is; xiThe optimal estimated value at the ith moment is used as an output value; siAs a prediction of the ith timeError covariance of the values; piThe error covariance of the ith moment; q is a preset process noise; kiIs the gain at time i; r is a preset observation error; ziIs the measured value at the ith time.

Description

Magnetic detection signal linear noise filtering method and system, computer readable storage medium, magnetic navigation sensor and AGV trolley
Technical Field
The invention relates to the technical field of AGV magnetic navigation.
Background
The technical principle of AGV magnetic navigation is that a magnetic strip is arranged at a preset position in advance, and the magnetic field intensity of the current position is detected through a magnetic sensor so as to position the current position. The magnetic sensor detects the magnetic field strength by measuring voltage by a magnetic induction element using the principle of electromagnetic induction and converting the measured voltage into the magnetic field strength.
The original voltage signal measured by the sensor is an analog signal, and is converted into a digital signal through analog-to-digital conversion, and then the final signal is obtained through twice filtering. In the two filtering, the first filtering is to filter out large noise; the second filtering is to filter linear noise, and the median filtering is also usually adopted in the prior art.
AGV magnetic navigation technique is by wide application in AGV transfer robot, for raising the efficiency, there is higher requirement to AGV transfer robot's functioning speed now, in the filtering process who gets rid of linear noise, the median filtering mode needs to be averaged N group data (be the data of N constantly when handling digital signal), the data bulk that needs to handle is big, the operand is also great, it has great capacity to require memory (RAM), the arithmetic speed is slower, can't satisfy the technological requirement of AGV magnetic navigation device faster response now.
Disclosure of Invention
In view of the above, the present invention provides a method and a system for filtering linear noise of a magnetic detection signal, a computer readable storage medium, a magnetic navigation sensor, and an AGV cart, which are faster in response.
In order to achieve the above object, the present invention provides the following technical solutions.
1. The magnetic detection signal linear noise filtering method comprises the following steps:
step 1: let Yi=Xi-1
Step 2: calculating Si=Pi-1+Q;
And step 3: calculating Ki=Si*(Si+R)-1
And 4, step 4: meterCalculate Xi=Yi+Ki*(Zi-Yi);
And 5: calculating Pi=(1-Ki)*Si
i is the serial number of the moment of the input digital signal; y isiThe predicted value of the magnetic detection signal at the ith moment is obtained; xiThe optimal estimated value of the magnetic detection signal at the ith moment is used as the output value of the magnetic detection signal at the ith moment after linear noise is filtered; siError covariance of predicted value of magnetic detection signal at ith moment; piThe error covariance of the magnetic detection signal at the ith moment; q is a preset process noise; kiIs the gain at time i; r is a preset observation error; ziIs the measured value of the magnetic detection signal at the ith moment;
at the initial time, for Xi-1、Pi-1And respectively carrying out assignment, and respectively executing the steps 1 to 5 for each moment i in sequence.
In the process of filtering linear noise, the filtering method only needs to use data at the current moment and data at the previous moment, and the median filtering mode needs to use data at N moments. Compared with a median filtering mode, the filtering mode disclosed by the invention has the advantages that the output signal is the optimal estimation of the predicted value and the measured value, the influence of linear noise is effectively reduced through error covariance iteration, and the measurement precision of a measurement unit is improved. The median filtering is an error of average linear noise, and the measurement precision cannot be improved, so that the data output by the filtering method is more accurate.
2. The magnetic detection signal linear noise filtering method according to claim 1, comprising the following steps of: calculate | Yi-ZiIf Yi-ZiIf | is greater than B, let XiIs a preset value, otherwise, X is calculatedi=Yi+Ki*(Zi-Yi) And B is a preset jump difference value. On signal transitionsFor example, when the computer is just started, the signal output by the filtering method of the technical scheme 1 has poor follow-up performance and is not fast enough in response. | Yi-ZiWhen | is greater than B, it indicates the signal jump, at this time, directly gives XiAnd assignment and output are performed, so that the following performance of output signals is improved, and the response speed is improved.
3. In the magnetic detection signal linear noise filtering method according to claim 2, B is 5mV or an amplification value corresponding thereto.
4. The method for filtering linear noise of magnetic detection signal according to claim 2 or 3, wherein in step 4, if Y is greater thani-ZiIf | is greater than B, let Xi=Zi. At the signal jump, the measured value Z of the magnetic probe signal at that moment in time is measurediDirectly assigning to the optimal estimated value X at the momentiThe output, measured value, although it may contain noise, is most likely to reflect the actual data of the current magnetic detection signal than other artificially set values, so the value is relatively more accurate than the output data.
5. A computer-readable storage medium storing a computer program, which when executed, can implement the magnetic detection signal linear noise filtering method according to any one of claims 1 to 4.
6. The magnetic detection signal linear noise filtering system comprises a computer readable storage medium and a processor, wherein the computer readable storage medium is the computer readable storage medium described in the technical scheme 5, and the processor can execute the computer program.
7. Magnetic navigation sensor, including technical scheme 6 the linear noise filtering system of magnetism detected signal.
8.AGV dolly, including technical scheme 7 the magnetic navigation sensor.
Drawings
FIG. 1 is a flow chart of a magnetic probe signal linear noise filtering method according to the present invention.
Detailed Description
The invention is described in detail below with reference to specific embodiments.
The AGV dolly of this embodiment, including magnetic navigation sensor, magnetic navigation sensor includes a plurality of magnetic induction element and signal processing system, and signal processing system includes the linear noise filtering system of magnetism detection signal. In other embodiments, the signal processing system may not be included within the sensor. Magnetic navigation sensor includes 16 magnetic induction element in this embodiment, and magnetic induction element can be hall element, and these 16 magnetic induction element transversely arranges along the equidistant interval of straight line, and in the scene of using, the magnetic stripe is for vertically arranging. The current position of the AGV trolley is positioned by utilizing the magnetic field intensity respectively detected by the plurality of magnetic induction elements which are transversely arranged, so that the AGV trolley is navigated.
The signal detected by each magnetic induction element is an analog signal (magnetic detection signal) representing a voltage signal, and the signal processing system needs to convert the analog signal into a digital signal for subsequent processing. After the magnetic detection signal is converted into a digital signal, a first filtering is performed to filter out large noise, which is a prior art and is not described herein. Then, a second filtering is performed to filter out the linear noise. And respectively carrying out the operations on the signals detected by each magnetic induction element, thereby finally converting the magnetic field intensity of the current position of the magnetic induction element.
Taking one magnetic induction element as an example, the processing method for the signals detected by each magnetic induction element is the same. In this embodiment, the magnetic detection signal linear noise filtering system applies a filtering method for filtering linear noise of a magnetic detection signal, which includes:
step 1: let Yi=Xi-1
Step 2: calculating Si=Pi-1+Q;
And step 3: calculating Ki=Si*(Si+R)-1
And 4, step 4: calculating Xi=Yi+Ki*(Zi-Yi);
And 5: calculating Pi=(1-Ki)*Si
i is the time sequence number of the input digital signal, i.e. the signal obtained after the first filtering is used as the input signal of the second filtering and is not compared with the continuous analog signalSimilarly, the digital signal is a signal at a plurality of discrete time intervals, i is a serial number indicating the time of the input digital signal; y isiThe predicted value of the magnetic detection signal at the ith moment is obtained; xiThe optimal estimated value of the magnetic detection signal at the ith moment is used as the output value of the magnetic detection signal at the ith moment after linear noise is filtered; siError covariance of predicted value of magnetic detection signal at ith moment; piThe error covariance of the magnetic detection signal at the ith moment; q is a preset process noise; kiIs the gain at time i; r is a preset observation error; ziIs the measured value of the magnetic detection signal at the ith moment;
at the initial time, for Xi-1、Pi-1And respectively carrying out assignment, and respectively executing the steps 1 to 5 for each moment i in sequence. That is, as shown in fig. 1, steps 1-5 are cyclic, once per time i.
In the process of filtering linear noise, only data of the current time i and data of the previous time i-1 need to be used, and the median filtering mode needs to use data of N times (generally 10), compared with the filtering method, the filtering method has the advantages of smaller data quantity to be processed, smaller calculation quantity, lower capacity requirement on a memory (RAM), quicker response and capability of meeting the technical requirement of quicker response of the conventional AGV magnetic navigation device. Compared with a median filtering mode, the filtering mode disclosed by the invention has the advantages that the output signal is the optimal estimation of the predicted value and the measured value, the influence of linear noise is effectively reduced through error covariance iteration, and the measurement precision of a measurement unit is improved. The median filtering is an error of average linear noise, and the measurement precision cannot be improved, so that the data output by the filtering method is more accurate.
At the signal jump, for example, when the computer is just started, the signal output by the filtering method has poor following performance and is not fast enough in response. In this case, a judgment step is added as a sub-step in step 4 to judge | Yi-ZiL (| (i.e. Y)i-and ZiAbsolute value of the difference between) is greater than a predetermined jump difference B, if Yi-ZiWhen | is greater than B, it indicatesThe signal jumps, when it is directly given to XiAnd assignment and output are performed, so that the following performance of output signals is improved, and the response speed is improved. If Yi-ZiIf | is less than or equal to B, then calculate Xi=Yi+Ki*(Zi-Yi). In this embodiment, B is 5mV or an amplification value corresponding thereto, and if the signal is processed after being amplified 10000 times, the value of B is 50.
In this embodiment, further, if | Yi-ZiWhen | is greater than B, let Xi=ZiAt the signal jump, the measured value Z of the magnetic probe signal at that moment in time is measurediDirectly assigning to the optimal estimated value X at the momentiThe output, measured value, although it may contain noise, is most likely to reflect the actual data of the current magnetic detection signal than other artificially set values, so the value is relatively more accurate than the output data.
The filtering method can be written into a computer program and stored in a computer readable storage medium, the computer readable storage medium can be used as a part of the magnetic detection signal linear noise filtering system, the magnetic detection signal linear noise filtering system is applied to a magnetic navigation sensor, and the magnetic navigation sensor is applied to an AGV, so that the response of the AGV is faster, and the working efficiency is higher.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (8)

1. The linear noise filtering method for the magnetic detection signal is characterized by comprising the following steps of:
step 1: let Yi=Xi-1
Step 2: calculating Si=Pi-1+Q;
And step 3: calculating Ki=Si*(Si+R)-1
And 4, step 4: calculating Xi=Yi+Ki*(Zi-Yi);
And 5: calculating Pi=(1-Ki)*Si
i is the serial number of the moment of the input digital signal; y isiThe predicted value of the magnetic detection signal at the ith moment is obtained; xiThe optimal estimated value of the magnetic detection signal at the ith moment is used as the output value of the magnetic detection signal at the ith moment after linear noise is filtered; siError covariance of predicted value of magnetic detection signal at ith moment; piThe error covariance of the magnetic detection signal at the ith moment; q is a preset process noise; kiIs the gain at time i; r is a preset observation error; ziIs the measured value of the magnetic detection signal at the ith moment;
at the initial time, for Xi-1、Pi-1And respectively carrying out assignment, and respectively executing the steps 1 to 5 for each moment i in sequence.
2. The magnetic probe signal linear noise filtering method of claim 1, wherein: and 4, step 4: calculate | Yi-ZiIf Yi-ZiIf | is greater than B, let XiIs a preset value, otherwise, X is calculatedi=Yi+Ki*(Zi-Yi) And B is a preset jump difference value.
3. The method of claim 2, wherein B is 5mV or an amplification value corresponding thereto.
4. A method of linear noise filtering of a magnetic probe signal as claimed in claim 2 or 3, characterized in that in step 4 if Y isi-ZiIf | is greater than B, let Xi=Zi
5. Computer readable storage medium, in which a computer program is stored, which computer program is able to carry out the method for linear noise filtering of a magnetic probe signal according to any one of claims 1 to 4 when executed.
6. A system for filtering linear noise of a magnetic probe signal, comprising a computer-readable storage medium and a processor, wherein the computer-readable storage medium is the computer-readable storage medium of claim 5, and the processor is capable of executing the computer program.
7. A magnetic navigation sensor comprising the magnetic probe signal linear noise filtering system of claim 6.
An AGV cart comprising the magnetic navigation sensor of claim 7.
CN202111325177.5A 2021-11-10 2021-11-10 Magnetic detection signal linear noise filtering method and system, computer readable storage medium, magnetic navigation sensor and AGV trolley Pending CN114046785A (en)

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CN1358318A (en) * 2000-01-14 2002-07-10 松下电器产业株式会社 Line filter
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CN107387064A (en) * 2017-07-27 2017-11-24 河南科技学院 A kind of new explosive-removal robot tunnel enters localization method
CN108759846A (en) * 2018-05-29 2018-11-06 东南大学 Adaptive extended kalman filtering noise model method for building up
CN109559334A (en) * 2018-11-23 2019-04-02 广州路派电子科技有限公司 Lane line method for tracing based on Kalman filter
CN109871508A (en) * 2019-03-14 2019-06-11 杭州电子科技大学 There are the centralized two stages kalman estimate methods of correlated measurement noise
US20200208980A1 (en) * 2017-07-28 2020-07-02 Sysnav Method and device for characterising a heading determined from the measurement of the magnetic field
CN112269192A (en) * 2020-10-22 2021-01-26 云南航天工程物探检测股份有限公司 Fast self-adaptive dynamic Beidou monitoring real-time resolving denoising method
CN112595327A (en) * 2020-12-25 2021-04-02 燕山大学 Positioning method and device based on UWB indoor positioning system

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1358318A (en) * 2000-01-14 2002-07-10 松下电器产业株式会社 Line filter
US20170110015A1 (en) * 2015-01-28 2017-04-20 Lockheed Martin Corporation Magnetic navigation methods and systems utilizing power grid and communication network
CN107387064A (en) * 2017-07-27 2017-11-24 河南科技学院 A kind of new explosive-removal robot tunnel enters localization method
US20200208980A1 (en) * 2017-07-28 2020-07-02 Sysnav Method and device for characterising a heading determined from the measurement of the magnetic field
CN108759846A (en) * 2018-05-29 2018-11-06 东南大学 Adaptive extended kalman filtering noise model method for building up
CN109559334A (en) * 2018-11-23 2019-04-02 广州路派电子科技有限公司 Lane line method for tracing based on Kalman filter
CN109871508A (en) * 2019-03-14 2019-06-11 杭州电子科技大学 There are the centralized two stages kalman estimate methods of correlated measurement noise
CN112269192A (en) * 2020-10-22 2021-01-26 云南航天工程物探检测股份有限公司 Fast self-adaptive dynamic Beidou monitoring real-time resolving denoising method
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Application publication date: 20220215