CN115290125B - Method for signal trimming by injecting random noise and magnetic encoder - Google Patents
Method for signal trimming by injecting random noise and magnetic encoder Download PDFInfo
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Abstract
The application belongs to the technical field of detection processing of magnetic field signals and provides a method for injecting random noise to carry out signal processingThe method for number trimming and the magnetic encoder comprise the following steps: pre-storing a trimming reference table, wherein the trimming reference table comprises a plurality of groups of reference points and trimming values y which are in one-to-one correspondence cal The difference value of adjacent reference points is C; obtaining a detection value y det (ii) a Injecting random noise y noise Obtaining a noisy value y mix =y det +y noise (ii) a According to the noise value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal Calculating a first correction value y cor =y mix +y cal (ii) a For the first correction value y cor Low-pass filtering to obtain a second correction value y' cor (ii) a Random noise y noise Is the detected value y det More than 2 times of the sampling frequency of (2), random noise y noise Has an amplitude of C, and a random noise of y noise The mathematical expectation of (a) is 0. The method for signal trimming by injecting random noise does not need complex multiplication-division operation, can realize data operation through a digital circuit, thereby obtaining higher signal trimming efficiency and effectively reducing the calculation cost.
Description
Technical Field
The present application relates to the field of magnetic field signal detection, and more particularly, to a method for signal modification by injecting random noise and a magnetic encoder.
Background
Magnetic sensors for detecting linear displacement or rotational angle often have different errors at different displacements or angles due to manufacturing errors or environmental factors. To correct for these errors, the detected values are typically compensated by means of a look-up table.
Taking an angle sensor as an example, taking N reference points, REF [1], REF [2]. REF [ i ]. A. The errors OFS [1], OFS [2]. Of each reference point are measured through the actual operation of a magnetic sensor, and the errors OFS [ N ], REF [ i ] correspond to the OFS [ i ] one by one. When the detection angle is equal to REF [ i ], the detection angle is added to the OFS [ i ] output, thereby obtaining a correction angle equal to REF [ i ] + OFS [ i ]. When the detection angle DET [ x ] is between two reference points REF [ i ], REF [ i +1], the distance from the detection angle DET [ x ] to REF [ i ] is n, the distance from the detection angle DET [ x ] to REF [ i +1] is p, and the nonlinear correction value at the position can be obtained through linear interpolation: OFS [ x ] = p/(n + p) × OFS [ i ] + n/(n + p) × OFS [ i +1]. The correction angle is equal to DET [ x ] + OFS [ x ].
The disadvantages of this linear interpolation method include:
1. each correction comprises complex multiplication and division, and the multiplication and division realized through the chip logic of the digital circuit needs to consume more time and has lower operation efficiency.
2. When the sampling speed of the sensor is very high (for example, up to 200 Mhz), each correction calculation is required to be completed in an extremely short clock period (5 ns), which is difficult to be realized for the 180nm technology commonly used for the chip, or huge chip area and power consumption are required.
Therefore, it is desirable to provide a signal error correction method that can reduce the computation cost.
Disclosure of Invention
The present application aims to provide a method for signal trimming by injecting random noise and a magnetic encoder, so as to solve the technical problem that more calculation cost is required to be consumed for signal error trimming in the prior art.
In order to achieve the purpose, the technical scheme adopted by the application is as follows: a method for injecting random noise to modify a signal is provided, which comprises the following steps:
pre-storing a trimming reference table, wherein the trimming reference table comprises a plurality of groups of reference points and trimming values y which are in one-to-one correspondence cal The difference value of adjacent reference points is C;
obtaining a detection value y det ；
Injecting random noise y noise Obtaining a noisy value y mix = y det +y noise ；
According to the noise value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal Calculating a first correction value y cor =y mix +y cal ；
For the first correction value y cor Low-pass filtering to obtain a second correction value y' cor ；
Wherein the random noise y noise Is the detected value y det More than 2 times of the sampling frequency of (2), random noise y noise Has an amplitude of C, and a random noise of y noise Is 0.
Alternatively, the detection value y det Has a sampling frequency of not less than 200MHZ and a random noise y noise Is the detected value y det 2 to 10 times the sampling frequency of (a).
Optionally, the function is according to a noisy value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal The method comprises the following steps: find and noise value y mix The closest reference point and the trimming value y corresponding to the closest reference point cal Calculating a first correction value y cor 。
Optionally, the trimming reference table contains m reference points, and the reference points are REF [ i [ ]]Is shown, wherein REF [1]]=0，REF[i+1]= REF[i]+2 K M, i and K are positive integers, i is more than or equal to 1 and less than or equal to m, and m is more than or equal to 2,K and more than or equal to 1.
Optionally, the noisy value y mix And the reference point is represented in binary, containing a noise value y mix And binary 2 K-1 Add to obtain y index Will y is index Compared with various reference points to find y index The closest reference point is used as the noise value y mix The closest reference point.
Alternatively, K =4, noisy value y mix And the number of binary bits of the reference point is greater than or equal to 8.
Optionally, the signal detection object of the method for performing signal modification by injecting random noise is an angle.
Optionally, the method for signal modification by injecting random noise implements data operation by using a hardware description language.
The application also provides a magnetic encoder which comprises a magnetic sensor and a signal processing circuit, wherein the signal processing circuit calculates the rotating angle of the external magnetic field relative to the magnetic sensor according to the method for performing signal trimming by injecting random noise.
Optionally, the signal processing circuit comprises a random number generator, a first adder, and a table look-up moduleA memory storing the trimming reference table, a second adder, and a low-pass filter, wherein the magnetic sensor outputs a detection value y det Detection value y det And random noise y output by the random number generator noise Adding the noise value y by a first adder mix Value y of noise mix Inputting the data to the table look-up module, wherein the table look-up module is used for looking up the table according to the noisy value y mix Inquiring corresponding trimming value y from the trimming reference table cal Value y of noise mix And the trimming value y cal The first correction value y is obtained by adding the second adder cor First correction value y cor Obtaining a second correction value y 'after filtering by the low-pass filter' cor 。
The method for signal modification by injecting random noise has the advantages that: compared with the prior art, the method has the advantages that the detection value y is detected det Injecting random noise y noise Obtaining a noisy value y mix Random noise y noise Is significantly larger than the detected value y det The sampling frequency of (2), the obtained noisy value y mix Is significantly larger than the detected value y det Because of random noise y noise Is 0, so the noisy value y mix With corresponding detection value y det Is uniformly distributed on both sides because of random noise y noise Has an amplitude of C, so that a certain detection value y det Generated noisy value y mix Necessarily covering at least one proximity to the detection value y det According to the noise value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal Calculating a first correction value y cor =y mix +y cal Then the first correction value y cor Can be uniformly distributed about a certain value for the first correction value y cor Low-pass filtering to obtain a second correction value y' cor Second correction value y' cor Can be used as the detection value y det More reliable correction results; the method for signal trimming by injecting random noise does not need to carry out complex multiplication-division operation, and can realize the operation of data through a digital circuitAnd higher signal trimming efficiency is obtained, and the calculation cost can be effectively reduced.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic view of a magnetic encoder according to an embodiment of the present disclosure.
Fig. 2 is a schematic diagram of a correspondence relationship between a reference point and a trimming value provided in an embodiment of the present application.
Wherein, in the figures, the various reference numbers:
11-a first adder, 12-a second adder.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element.
It will be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like, as used herein, refer to an orientation or positional relationship indicated in the drawings that is solely for the purpose of facilitating the description and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be considered as limiting the present application.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
Referring to fig. 1, a magnetic encoder according to an embodiment of the present application will now be described. The magnetic encoder comprises a magnetic sensor and a signal processing circuit, wherein the signal processing circuit calculates the rotating angle of an external magnetic field relative to the magnetic sensor according to a method for carrying out signal trimming by injecting random noise.
In some examples, the magnet rotates relative to the magnetic sensor, and the magnetic encoder detects the changing magnetic signal via the magnetic sensor and provides the detected magnetic signal to the signal processing circuit. The magnetic sensor may be a magnetoresistive effect sensor, a hall effect sensor, or the like that is capable of detecting a changing magnetic signal. The magnetic sensor may be present as a packaged chip or as a structure inside the chip. In some examples, the magnetic sensor and the signal processing circuit may be integrated together on the same chip, and the chip may be referred to as a magnetic encoder, magnetic encoding for short. In other examples, the magnetic encoder may be presented as a PCBA with the magnetic sensor and the signal processing circuitry being circuit components on the PCBA.
The signal processing circuit comprises a random number generator, a first adder 11, a table look-up module, a memory, a second adder 12 and a low-pass filter, wherein the memory stores a trimming reference table, and the magnetic sensor outputs a detection value y det Detection value y det And random noise y output by the random number generator noise The noisy value y is obtained by addition by a first adder 11 mix Value y of noise mix Inputting the data to a table look-up module, and the table look-up module is used for looking up the table according to the noisy value y mix Inquiring corresponding trimming value y from the trimming reference table cal Is composed ofNoise value y mix And the trimming value y cal The first correction value y is obtained by adding the second adder 12 cor First correction value y cor Obtaining a second correction value y 'after being filtered by a low-pass filter' cor . The random number generator, the first adder 11, the table look-up module, the memory, the second adder 12 and the low-pass filter included in the signal processing circuit can be realized by a hardware description language, and the data operation of the method for performing signal trimming by injecting random noise can obtain higher efficiency.
The following describes a method for performing signal modification by injecting random noise according to an embodiment of the present application. The signal detection object of the method is linear displacement or rotation angle.
The method for signal modification by injecting random noise needs to use a modification reference table, and the modification reference table contains a plurality of groups of reference points and modification values y which are in one-to-one correspondence cal And the difference value of adjacent reference points is C.
The method for injecting random noise to carry out signal modification comprises the following steps:
obtaining a detection value y det ；
Injecting random noise y noise Obtaining a noisy value y mix = y det +y noise ；
According to the noise value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal Calculating a first correction value y cor =y mix +y cal ；
For the first correction value y cor Low-pass filtering to obtain a second correction value y' cor ；
Wherein, random noise y noise Is the detected value y det More than 2 times of the sampling frequency of (2), random noise y noise Amplitude of C, random noise y noise The mathematical expectation of (a) is 0.
The method for signal modification by injecting random noise has the advantages that: compared with the prior art, the method and the device have the advantages that the detection value y is detected det Injecting random noise y noise Obtaining a noisy value y mix Random noise y noise Is significantly larger than the detected value y det The sampling frequency of (2), the obtained noisy value y mix Is significantly larger than the detected value y det Because of random noise y noise Is 0, so the noisy value y mix With corresponding detection value y det Is uniformly distributed on both sides because of random noise y noise Has an amplitude of C, so that a certain detection value y det Generated noisy value y mix Necessarily covering at least one proximity to the detection value y det According to the noise value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal Calculating a first correction value y cor =y mix +y cal Then the first correction value y cor Can be uniformly distributed about a certain value for the first correction value y cor Low-pass filtering to obtain a second correction value y' cor Second correction value y' cor Can be used as the detection value y det More reliable correction results; the method for signal trimming by injecting random noise does not need complex multiplication-division operation, can realize data operation through a digital circuit, thereby obtaining higher signal trimming efficiency and effectively reducing the calculation cost.
The method for signal modification by injecting random noise provided by the application is used for detecting value y det The sampling frequency of (a) is not particularly required. When the detected value y is det When the sampling frequency is higher, the advantages of the method are more prominent compared with the prior art, and excellent signal trimming efficiency can be obtained. In some examples, detection value y det Is not less than 200MHZ.
Random noise y noise Is 0 and has a magnitude C, i.e. a magnitude equal to the difference between adjacent reference points in the trimming reference table. Random noise y noise Can be generated by a random function because of the random noise y noise Is 0, so the noisy value y mix With corresponding detection value y det Are uniformly distributed on both sides of the center.
And the detected value y det Compared with the sampling frequency of the random noise y noise The frequency spectrum of (a) needs to be within a reasonable range. If random noise y noise If the frequency spectrum of (A) is too low, the noise value y is contained mix And a first correction value y cor A uniform divergence may not be obtained resulting in distortion of the trimming result. If random noise y noise Is too high, random noise y is generated noise The algorithm of (a) is more complex or the requirement on hardware is higher. Preferably, the random noise y noise Is the detected value y det The sampling frequency is 2 to 10 times, and a better trimming result can be obtained. In practical application, the random noise y output by the random number generator noise The frequency of (a) is often not pure, here said random noise y noise The spectrum of (c) refers to the dominant frequency, or center frequency, of noise as is understood colloquially by those skilled in the art. In some cases, random noise y noise Also known as pseudo random noise.
Referring to FIG. 2, assume that the detected value y is det At a first reference point REF 1 And a second reference point REF 2 In between, detection value y det To a first reference point REF 1 Is n, and the detected value y det To a second reference point REF 2 Is p, C = n + p, first reference point REF 1 Corresponding to the first trimming value y cal1 Second reference point REF 2 Corresponding to the second trimming value y cal2 。
If the existing linear interpolation method is adopted, the noisy value y is mix The corresponding modification value is p/(n + p) × y cal1 +n/(n+p)* y cal2 。
The algorithm comprises complex multiplication and division, and the multiplication and division are realized through chip logic of a digital circuit, so that more time is consumed, and the operation efficiency is low. This application attempts to avoid such calculations involving complex multiplication and division.
The application is based on the noisy value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal The following two cases are included:
the first condition is as follows: find and noise value y mix The closest reference point and the trimming value y corresponding to the closest reference point cal Calculate the first correctionPositive value y cor . If the second reference point REF 2 Closer to the noisy value y mix I.e. n > p, to a second reference point REF 2 Corresponding trimming value y cal2 Calculating a first correction value y cor . If containing the noise value y mix Exactly equal to a certain reference point (n =0, or p = 0), that is, the noise-containing value y mix The closest reference point, and the first correction value y is calculated according to the modification value corresponding to the reference point cor 。
Case two: first reference point REF 1 And a second reference point REF 2 For two adjacent reference points, if the noise value y mix To a first reference point REF 1 And a second reference point REF 2 Is equal, i.e. n = p, let y cal = y cal1 Or y is cal = y cal2 Or y is cal =( y cal1 + y cal2 )/2。
Noisy value y mix Uniformly distributed on the detection value y with the same probability det On the left and right sides, i.e. the interval [ y det -C/2，y det +C/2]And (4) the following steps.
Assuming noisy values y mix Falls within the interval A [ y det -C/2，REF 1 +C/2]Internal, noisy value y mix Closer to REF 1 Should take y cal1 As trimming value y cal (ii) a Width of interval a = REF 1 +C/2-（y det -C/2）=C-n=p，y mix The probability of falling within the interval A is p/(n + p).
Assuming noisy value y mix Falls within an interval B [ REF 1 +C/2，y det +C/2]Internal, noisy value y mix Closer to REF 2 Should take y cal2 As trimming value y cal (ii) a Width of section B = y det +C/2-（REF 1 +C/2）= n，y mix The probability of falling within the interval B is n/(n + p).
Then in the interval [ y det -C/2，y det +C/2]Inner, trimming value y cal Is p/(n + p) × y cal1 +n/(n+p)* y cal2 That is, the modification value y obtained by the method for signal modification by injecting random noise provided by the present application cal The mathematical expectation of (c) is equal to the trim value calculated according to the existing linear interpolation method.
The modification value y can also be derived according to the following formula cal Mathematical expectation of (1):
wherein
Is a random probability density.
For case two, i.e. n = p, the probability is very small, in which case let y cal = y cal1 、y cal = y cal2 Or y cal =( y cal1 + y cal2 ) And/2 is possible without substantial influence on the operation result.
How to find the noise value y is described below mix The closest reference point.
Suppose that the trimming reference table contains m reference points, which are REF [ i ]]Is shown, wherein REF [1]]=0，REF[i+1]= REF[i]+2 K I.e. C =2 K M, i and K are positive integers, i is more than or equal to 1 and less than or equal to m, and m is more than or equal to 2,K and more than or equal to 1.REF [1]]=0，C=2 K Is advantageous in that 2 K When represented in binary, only one of the bits is 1 and the other bits are 0. In this case, the respective reference points can be divided into two parts with this bit of 1: a comparison section (high order) and a reserve section (low order), the bit of 1 belonging to the comparison section. Noisy value y mix The noise value y is divided into a comparison part (high order bits) and a remaining part (low order bits) correspondingly mix The comparison portion of (a) may be compared with the comparison portion of the reference point.
Further, the noisy value y mix And the reference point is represented in binary, containing a noise value y mix And binary 2 K-1 Add to obtain y index Will y is index Compare with various reference points to find y index The closest reference point, andtaking the reference point as the noise value y mix The closest reference point. Noisy value y mix And binary 2 K-1 Addition, corresponding to a decimal "rounding", 2 K-1 And a noise value y mix After addition, if there is no carry, the noisy value y mix The comparison part of (1) is unchanged, which is equivalent to 'four houses'; if carry is present, the noise value y is contained mix The comparison portion of (1) is added, corresponding to "five in".
Preferably, K =4, noisy value y mix And the number of binary bits of the reference point is greater than or equal to 8. Noisy value y mix And the number of binary bits of the reference point may be 8, 12, 16, 20, 24, 28, or 32, etc.
Table 1 shows an example of the reference point.
TABLE 1
In the example shown in table 1, C =2 K =16,k =4, noise value y mix The number of binary bits of the sum reference point is 8, including the noise value y mix And the high 4 bits of the reference point are comparison parts, and the low 4 bits are remaining parts. 2 K-1 Is represented as 00001000. Assume a first noisy value y mix1 00010001 (decimal 17), then y index1 =y mix1 +2 K-1 =00010001+00001000=00011001, with y index1 The highest 4 bits of (b) can quickly find the closest 00010000 (16 decimal) compared with the highest 4 bits of the reference point. Assume a second noisy value y mix2 00011101 (decimal 29), then y index2 =y mix2 +2 K-1 =00011101+00001000=00100101, using y index2 The highest 4 bits of (b) and the highest 4 bits of the reference point can quickly find the closest 00100000 (32 decimal).
In some examples, the upper 4 bits of each reference point may be used as its sequence number, and y may be used index The high 4 bits of the reference point are compared with the serial numbers of all the reference points to quickly find the closest reference point.
It is noted that the units of reference points listed in table 1 are not degrees, and the values given do not directly indicate angle in degrees. For the convenience of binary representation, 2 may be used R Representing 360 deg., R being a positive integer. For example, let R =8, 360 ° by 256 (100000000 binary), 180 ° by 128 (10000000 binary), and 22.5 ° by 16 (00010000 binary). In this example, assuming that the binary storage bit number is 8 bits, 256 (binary is 100000000) indicates 360 °,100000000 will overflow and become 00000000, and considering that 360 ° coincides with 0 °, it is also possible to indicate 360 ° or 0 ° by 000000000000 in practical application.
First correction value y cor =y mix +y cal First correction value y cor Containing random noise y noise The second correction value y 'is more reliable after low-pass filtering by the low-pass filter' cor . The low-pass filter of the present application can employ existing techniques. For example, the low-pass filter can be used directly in the conventional sensor signal processing system to remove the true noise from the signal, the true noise and the random noise y added for the non-linear modification noise After linear superposition, the signals can be synchronously removed in a same low-pass filter.
Preferably, the method for signal modification by injecting random noise realizes the operation of data through a hardware description language.
In order to obtain excellent operation speed, a hardware description language is applied in one embodiment of the present application, and the method for injecting random noise to perform signal modification can implement data operation through the hardware description language. It is understood that the method of injecting random noise to modify the signal may also implement the operation of the data in other ways. The Hardware Description language applied in the present application may be VHDL (Very-HiCh-Speed Integrated Circuit Hardware Description LanCuaCe) or Verilog HDL. Compared with the calculation of a microprocessor MCU, the integrated circuit finally generated by using the hardware description language has the obvious advantage of high parallel operation speed. In terms of mathematical calculation, the calculation speed of general multiplication or general division between any numbers with larger data bit numbers in an integrated circuit is relatively slow through a hardware description language, and the cost of consumed hardware is too large, so that the complex multiplication-division calculation is avoided as much as possible. It should be noted that, in the hardware description language, when calculating, the division and multiplication of the exponent of 2 are implemented using shift operations, so the calculation speed of the division and multiplication of the exponent of 2 is also faster.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (9)
1. A method for signal modification by injecting random noise, comprising:
pre-storing a trimming reference table, wherein the trimming reference table comprises a plurality of groups of reference points and trimming values y which are in one-to-one correspondence cal The difference value of adjacent reference points is C;
obtaining a detection value y det ；
Injecting random noise y noise Obtaining a noisy value y mix ＝y det +y noise ；
According to the noise value y mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal Calculating a first correction value y cor ＝y mix +y cal ；
For the first correction value y cor Low-pass filtering to obtain a second correction value y' cor ；
Wherein the random noise y noise Is the detected value y det More than 2 times of the sampling frequency of (2), random noise y noise Amplitude of C, random noise y noise Is 0;
and, the noise value y is determined according to mix Inquiring the trimming reference table to obtain a corresponding trimming value y cal The method comprises the following steps: find and noise value y mix The closest reference point and the trimming value y corresponding to the closest reference point cal Calculate the first correctionPositive value y cor 。
2. The method of injecting random noise for signal modification as set forth in claim 1, wherein:
detection value y det Has a sampling frequency of not less than 200MHz and a random noise y noise Is the detected value y det 2 to 10 times the sampling frequency of (a).
3. The method of injecting random noise for signal modification as set forth in claim 1, wherein:
the trimming reference table contains m reference points, and the reference points are REF [ i]Is shown, wherein REF [1]]＝0，REF[i+1]＝REF[i]+2 K M, i and K are positive integers, i is more than or equal to 1 and less than or equal to m, and m is more than or equal to 2,K and more than or equal to 1.
4. The method of injecting random noise for signal modification as set forth in claim 3, wherein:
value y containing noise mix And the reference point is represented in binary, containing a noise value y mix And binary 2 K-1 Add to obtain y index Will y is index Compared with various reference points to find y index The closest reference point is used as the noise value y mix The closest reference point.
5. The method of injecting random noise for signal modification as set forth in claim 4, wherein:
k =4, noisy value y mix And the number of binary bits of the reference point is greater than or equal to 8.
6. The method of any of claims 1 to 5, wherein the method further comprises:
the signal detection object of the method for signal modification by injecting random noise is an angle.
7. The method of any of claims 1 to 5, wherein the method further comprises:
the method for signal trimming by injecting random noise realizes the operation of data through a hardware description language.
8. A magnetic encoder, characterized by:
the magnetic encoder comprises a magnetic sensor and a signal processing circuit, wherein the signal processing circuit calculates the rotation angle of an external magnetic field relative to the magnetic sensor according to the method for injecting random noise for signal trimming, which is disclosed by any one of claims 1 to 7.
9. The magnetic encoder of claim 8, wherein:
the signal processing circuit comprises a random number generator, a first adder, a table look-up module, a memory, a second adder and a low-pass filter, wherein the memory stores the trimming reference table, and the magnetic sensor outputs a detection value y det Detection value y det And random noise y output by the random number generator noise Adding the noise value y by a first adder mix Value y of noise mix Inputting the data to the table look-up module, wherein the table look-up module is used for looking up the table according to the noisy value y mix Inquiring corresponding trimming value y from the trimming reference table cal Value y of noise mix And the trimming value y cal The first correction value y is obtained by adding the second adder cor First correction value y cor Obtaining a second correction value y 'after filtering by the low-pass filter' cor 。
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