CN110830003A - Filtering method based on α - β filter - Google Patents
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- CN110830003A CN110830003A CN201911062547.3A CN201911062547A CN110830003A CN 110830003 A CN110830003 A CN 110830003A CN 201911062547 A CN201911062547 A CN 201911062547A CN 110830003 A CN110830003 A CN 110830003A
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- 238000001914 filtration Methods 0.000 title claims abstract description 77
- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000005259 measurement Methods 0.000 claims description 84
- 238000004590 computer program Methods 0.000 claims description 8
- 238000012937 correction Methods 0.000 claims description 6
- 239000004576 sand Substances 0.000 claims description 3
- 238000009499 grossing Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000000354 decomposition reaction Methods 0.000 description 1
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
- H03H17/00—Networks using digital techniques
- H03H17/0009—Time-delay networks
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
- H03H17/00—Networks using digital techniques
- H03H17/02—Frequency selective networks
- H03H17/0219—Compensation of undesirable effects, e.g. quantisation noise, overflow
Abstract
The disclosure relates to a filtering method based on a α - β filter, which comprises the steps of outputting filtering parameters according to an interval between two previous and next measuring moments, wherein the filtering parameters comprise an α parameter and a β parameter, filtering a measuring increment value and filtering a measured value through an α - β filter unit according to the filtering parameters, a filtering output value corresponding to the previous moment and a measured value at the current moment, outputting a measuring increment filtering value and a measuring filtering value, and outputting a filtering output value corresponding to the current moment according to the measuring increment filtering value, the measuring filtering value and the interval between the two previous and next measuring moments.
Description
Technical Field
The disclosure relates to a filtering method, in particular to a method for filtering signal measurement data in the field of wireless indoor and outdoor positioning.
Background
In the field of wireless indoor positioning, a α - β filter can buffer the situation that the signal measurement value has large fluctuation, so that the signal measurement value is smoother, but because the traditional α - β filter can only be applied to the filtering of the measurement value at equal time intervals, a large error can be caused to the measurement value at unequal time intervals.
The conventional α - β filter also causes the problem of measurement delay, i.e. the output value after filtering and the actual measurement value are delayed for a period of time, as shown in fig. 1a, for the case that the real-time requirement of signal measurement is high, the response delay phenomenon to the input signal is obvious after smoothing by the filter.
BRIEF SUMMARY OF THE PRESENT DISCLOSURE
The filter method based on the α - β filter comprises the steps of outputting filter parameters according to an interval between two previous and next measurement moments, wherein the filter parameters comprise α parameters and β parameters, filtering a measurement increment value and a measurement value through a α - β filter unit according to the filter parameters, a filter output value corresponding to the previous moment and a measurement value at the current moment, outputting a measurement increment filter value and a measurement filter value, and outputting a filter output value corresponding to the current moment according to the measurement increment filter value, the measurement filter value and the interval between the two previous and next measurement moments.
Preferably, the filter parameter is expressed by the following formula:
wherein, TsAnd a is a preset filter coefficient for the interval between the front measurement moment and the rear measurement moment.
Preferably, the filter output value corresponding to the current time is represented by the following formula:
is the filtering output value corresponding to the current time,
in order to measure the value of the filtering,
for measuring incremental filtered values, TsThe two measurement time intervals are front and back.
According to another aspect of the disclosed embodiment, the α - β filter further comprises a filtering parameter generating unit, a α - β filter unit and a filtering delay correcting unit, wherein the filtering parameter generating unit outputs filtering parameters according to an interval between two previous and next measuring time moments, the filtering parameters comprise α parameters and β parameters, the α - β filter unit performs measurement increment value filtering and measurement value filtering through a α - β filter unit according to the filtering parameters, the filtering output value corresponding to the previous time moment and the current time moment measurement value, and outputs a measurement increment filtering value and a measurement filtering value, and the filtering delay correcting unit outputs a filtering output value corresponding to the current time moment according to the measurement increment filtering value, the measurement filtering value and the interval between the two previous and next measuring time moments.
According to another aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium storing a computer program for executing the above-described filtering method.
According to another aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including: a processor; a memory for storing processor-executable instructions; and the processor is used for reading the executable instructions from the memory and executing the instructions to realize the filtering method.
Compared with the prior art, the filter delay correction unit has the advantages that the problem that the traditional α - β filter can only measure the time interval at equal time is solved, the universality of the filter is improved, the α - β filter delay correction unit can correct the delay caused by filtering, and the real-time performance of the filter is improved.
Drawings
FIGS. 1a and 1b illustrate the results of filtering conventional α - β filters for measurements at equal and unequal intervals.
FIG. 2 is a schematic diagram of the input and output of the α - β filter of the present disclosure.
FIG. 3 is a graph of the results of filtering the non-equidistant time interval measurements by the α - β filter of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure. Embodiments of the invention are operational with numerous other general purpose or special purpose computing system environments or configurations, and with numerous other electronic devices, such as terminal devices, computer systems, servers, etc.
And 101, outputting filter parameters according to the interval between the front measurement time and the rear measurement time, wherein the filter parameters comprise α parameters and β parameters.
In this embodiment, the interval between two consecutive measurement time points refers to the interval time length between two consecutive signal measurements, the filter parameters are β 0 parameter and β 1 parameter in α - β filter, β 2- β 3 filter is a filter which can be used for state estimation and data smoothing, α parameter and β parameter refer to two adjustable parameters in the filter, the larger the α parameter and β parameter is, the faster the dynamic performance of the filter is, but the larger the noise is, the smaller the α parameter and β parameter is, the smaller the noise is, the smoother the filtered value is, but the dynamic performance is poor, therefore, a balance needs to be made between the dynamic performance and the filtered noise, and the optimal α parameter and β parameter need to be calculated.
The filter parameters in this embodiment are expressed by the following formula:
wherein, TsAnd a is a preset filter coefficient for the interval between the front measurement moment and the rear measurement moment.
It can be seen from the above formula that the longer the preceding and following filtering time intervals are, the higher the corresponding α weight is, the higher the weight of the current measurement value is, it is obvious that the present disclosure can generate different α - β filtering parameters for different measurement time intervals, i.e. for non-equal interval measurement time intervals, and the calculated filtering parameters are input into the α - β filter unit.
And 102, filtering the measurement increment value and the measurement value through an α - β filter unit according to the filter parameters, the filter output value corresponding to the previous moment and the measurement value at the current moment, and outputting the measurement increment filter value and the measurement filter value.
In the present embodiment, the α parameter and the β parameter calculated in step 101 are input into the α - β filter unit, and the α - β filter unit filters the filter output value corresponding to the previous time and the measured value at the current time according to the α parameter and the β parameter calculated in step 101, and outputs a measured incremental filter value and a measured filter value, wherein the measured filter value is obtained by filtering the measured value at the current time and the filter output value corresponding to the previous time, and the measured incremental filter value is obtained by filtering an incremental value between the measured value at the current time and the filter output value corresponding to the previous time.
Step 103: and outputting a filtering output value corresponding to the current moment according to the measurement increment filtering value, the measurement filtering value and the interval between the front measurement moment and the rear measurement moment.
In this embodiment, because the filter has a delay problem, the present disclosure designs a delay correction step, which compensates for the delay caused by filtering according to the filter delay correction formula, according to the measurement incremental filter value, the measurement filter value, and the interval between the previous and subsequent measurement times, and improves the real-time performance of the filter. The delay correction formula is as follows:
is the filtering output value corresponding to the current time,
in order to measure the value of the filtering,for measuring incremental filtered values, TsIs front and backTwo measurement time intervals.
Fig. 2 is a schematic structural diagram of a α - β filter provided in an exemplary embodiment of the disclosure, which may be applied to an electronic device, as shown in fig. 2, the β - β filter includes a filter parameter generating unit that outputs filter parameters according to two previous and subsequent measurement time intervals, wherein the filter parameters include a α parameter and a β parameter, a α - β filter unit that performs measurement increment value filtering and measurement value filtering through a α - β filter unit according to the filter parameters, a filter output value corresponding to a previous time and a current time measurement value, and outputs a measurement increment filter value and a measurement filter value, and a filter delay correcting unit that outputs a filter output value corresponding to a current time according to the measurement increment filter value, the measurement filter value and the two previous and subsequent measurement time intervals.
Fig. 3 shows the filtering effect of the improved filter according to the present disclosure, and it can be seen from the figure that under the condition of unequal intervals, the filter has a good smoothing effect, and there is no filtering delay, so that the dynamic real-time performance of the filter output value is improved.
The improved α - β filter disclosed by the disclosure generates the filter parameters of the unequal time measurement intervals through the α - β filter parameter generating unit, solves the problem that the traditional α - β filter can only measure the intervals at equal time, improves the universality of the filter, and improves the real-time performance of the filter because the α - β filter delay correcting unit can correct the delay caused by filtering.
The electronic device of the disclosed embodiments includes one or more processors and memory. The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. The memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. Volatile memory can include, for example, Random Access Memory (RAM), cache memory (or the like). The non-volatile memory may include, for example, Read Only Memory (ROM), a hard disk, flash memory, and the like. One or more computer program instructions may be stored on a computer-readable storage medium and executed by a processor to implement the filtering methods of the various embodiments of the disclosure above and/or other desired functions. Various contents such as an input signal, a signal component, a noise component, etc. may also be stored in the computer-readable storage medium.
In addition to the above-described methods and apparatus, embodiments of the present disclosure may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the filtering method according to various embodiments of the present disclosure described in the "exemplary methods" section above of this specification.
The computer program product may write program code for carrying out operations for embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform steps in a filtering method according to various embodiments of the present disclosure described in the "exemplary methods" section above of this specification.
It is also noted that in the devices, apparatuses, and methods of the present disclosure, each component or step can be decomposed and/or recombined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.
Claims (6)
1. A method of filtering based on α - β filters, comprising:
outputting filter parameters according to the interval between the front measurement time and the rear measurement time, wherein the filter parameters comprise α parameters and β parameters;
according to the filtering parameters, the filtering output value corresponding to the last moment and the measured value at the current moment, filtering the measurement increment value and the measured value through an α - β filter unit, and outputting a measurement increment filtering value and a measurement filtering value;
and outputting a filtering output value corresponding to the current moment according to the measurement increment filtering value, the measurement filtering value and the interval between the front measurement moment and the rear measurement moment.
2. The method of claim 1, wherein the filtering parameter is represented by the following formula:
wherein, TsAnd a is a preset filter coefficient for the interval between the front measurement moment and the rear measurement moment.
3. The method of claim 1, wherein the filtered output value corresponding to the current time is represented by the following formula:
4. An α - β filter, comprising:
the filter parameter generating unit outputs filter parameters according to the interval between the front measurement time and the rear measurement time, wherein the filter parameters comprise α parameters and β parameters;
α - β filter unit, the α - β filter unit carries out the filtration of measurement increment value and the filtration of measurement value through α - β filter unit according to the filter parameter, the filter output value corresponding to the last moment and the measurement value at the current moment, and outputs the measurement increment filtering value and the measurement filtering value;
and the filter delay correction unit outputs a filter output value corresponding to the current moment according to the measurement increment filter value, the measurement filter value and the interval between the front measurement moment and the rear measurement moment.
5. A computer-readable storage medium, the storage medium storing a computer program for performing the method of any of the preceding claims 1-3.
6. An electronic device, the electronic device comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method of any one of claims 1 to 3.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114337605A (en) * | 2022-03-14 | 2022-04-12 | 南京甄视智能科技有限公司 | Rotation angle filtering method, computer equipment and storage medium |
| CN116089779A (en) * | 2022-12-31 | 2023-05-09 | 南京星思半导体有限公司 | Processing method and device of filter coefficient, storage medium and filter equipment |
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| CN104052692A (en) * | 2013-03-14 | 2014-09-17 | 富士通半导体股份有限公司 | Data Signal Correction Circuit, Receiver, And Data Signal Correction Method |
| CN108805011A (en) * | 2018-04-24 | 2018-11-13 | 长江大学 | A kind of digital filtering method and system |
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| WO2002071256A1 (en) * | 2001-02-20 | 2002-09-12 | Brown University Research Foundation | Signal adaptive filter bank optimization |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114337605A (en) * | 2022-03-14 | 2022-04-12 | 南京甄视智能科技有限公司 | Rotation angle filtering method, computer equipment and storage medium |
| CN114337605B (en) * | 2022-03-14 | 2022-05-31 | 南京甄视智能科技有限公司 | Rotation angle filtering method, computer equipment and storage medium |
| CN116089779A (en) * | 2022-12-31 | 2023-05-09 | 南京星思半导体有限公司 | Processing method and device of filter coefficient, storage medium and filter equipment |
| CN116089779B (en) * | 2022-12-31 | 2023-10-13 | 南京星思半导体有限公司 | Processing method and device of filter coefficient, storage medium and filter equipment |
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Application publication date: 20200221 |