CN107870000A - Raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique - Google Patents
Raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique Download PDFInfo
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Abstract
Comprised the following steps the present invention relates to a kind of based on a kind of raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique, method:First, establish fitting of a polynomial compensation model;Second, choose fitting of a polynomial compensating parameter.The present invention establishes a kind of raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique.This method is based on multinomial compensation method, has quantified compensation relevant parameter, solves the problem that optical fibre gyro zero bias are easily influenceed by temperature change, reduces the influence of temperature on fiber Gyro Precision.Main contents involve setting up optical fibre gyro zero offset compensation fitting of a polynomial compensation model and choose two aspects of fitting of a polynomial compensating parameter.
Description
Technical field
The present invention relates to a kind of raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique.Belong to inertia
Navigation field.
Background technology
The factor for influenceing Gyro Precision has a lot, and key one of which is exactly gyro zero bias.Optical fibre gyro is no exception, so
And compared to for more other gyros, optical fibre gyro is more sensitive to temperature, and especially to optical fibre gyro zero bias, there is larger shadow
Ring, this also becomes the problem of optical fibre gyro engineering engineering application.
The influence for eliminating temperature on fiber gyro zero bias typically has two methods, first, the physical method handled firmly, passes through
Improve and change optical fibre gyro manufacturing process, while install accurate temperature control system etc. additional, but this method is to hardware and phase
Pass technological requirement is high, and superhigh precision optical fibre gyro typically exists only in the model machine stage of laboratory at present;Second, supple-settlement
Mathematical method, this method realize and are relatively easy to that but compensation method is various, it is difficult to quantify, consider during additionally, due to compensation because
Element is not comprehensive enough, and correction result is not ideal.
This method is based on Polynomial Fitting Technique technology, to optical fiber in terms of temperature, thermograde, rate of temperature change three
Gyro zero bias have carried out comprehensive quantization compensating approach, and gyro bias instaility increases substantially.
The content of the invention
The technical problems to be solved by the invention are to provide one kind for above-mentioned prior art to be based on Polynomial Fitting Technique
Raising optical fibre gyro bias instaility method, compensate for gyro zero offset error caused by temperature change, reduce temperature to top
The influence of spiral shell zero bias, improves Gyro Precision.
Technical scheme is used by the present invention solves the above problems:A kind of raising optical fiber based on Polynomial Fitting Technique
Gyro bias instaility method, the described method comprises the following steps:
Step 1: establish fitting of a polynomial compensation model
Temperature change is that the influence of temperature on fiber gyro zero bias is main an important factor for influenceing optical fibre gyro zero bias precision
Show three temperature, rate of temperature change and thermograde aspects.
1st, based on above three aspect factor, the temperature drift for gyro can be fitted using multinomial and establish model knot
Structure such as following formula:
In formula:
L---- gyros export, unit °/h.
L0After ----gyro starts, the zero bias output obtained by sampling in first two minutes, unit °/h.
The quick temperature of T---- gyros, unit DEG C
Δ T---- gyro thermogrades, unit DEG C
DT/dt---- gyro rate of temperature changes, unit DEG C/s
Ai、Bj、Cj----multinomial coefficient,
M, the highest power of each temperature factors of n----.
2nd, the coefficient A in model multinomiali、Bj、CjWith regression analysis least square fitting.Multinomial model is writeable
For:
L-L0=Ta (2)
Wherein:
Q is the exponent number of temperature drift model, and T is optical fibre gyro temperature matrices, and N is gyro temperature drift data amount check.
3rd, the coefficient fitted under different temperatures is different that each coefficient of Ai, Bj, Ck meets following relation in formula (1):
Step 2: choose fitting of a polynomial compensating parameter
1st, in actual use, to each gyro under different temperatures by least-squares calculation, it can obtain coefficient Aij (i
=1,2 ... q;J=0,1,2,3).It is solidificated in the test software of computer.As long as measure gyro after gyro startup to open
Initial temperature T when dynamic0, you can each coefficient in the model is calculated according to formula (3).
2 and then according to each temperature factor, the zero bias of current gyro are estimated using multinomial model formula (1), this is estimated
The zero bias gone out deduct, the zero bias after as compensating.
Preferably, in this method, temperature on fiber gyro zero bias are influenceed compensation and compensated using second order or quadravalence, thermograde
Compensation is influenceed on optical fibre gyro zero bias with rate of temperature change and uses first compensation phase.
Compared with prior art, the advantage of the invention is that:
The present invention is based on Polynomial Fitting Technique principle, establishes optical fibre gyro zero offset compensation mathematical modeling, passes through experiment
Comparing is quantified key coefficient in model, be compensate for gyro zero offset error caused by temperature change, is reduced temperature
The influence to gyro zero bias is spent, improves Gyro Precision.
Brief description of the drawings
Fig. 1 temperature test experimental facilities connection figures.
The polynomial fitting curve that Fig. 2 temperature influences on gyro zero bias.
2,4 rank multinomial compensated curves during Fig. 3 temperature consecutive variations.
Fig. 4 thermogrades and gyro zero bias relation.
Fig. 5 temperature, thermograde, rate of temperature change 2,4 rank compensated curves.
Embodiment
The present invention is described in further detail below in conjunction with accompanying drawing embodiment.
The present invention relates to a kind of raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique, method includes
Following steps:First, establish fitting of a polynomial compensation model;Second, choose fitting of a polynomial compensating parameter.
2nd, implementation process
Step 1: establish fitting of a polynomial compensation model
1st, based on above three aspect factor, the temperature drift for gyro can be fitted using multinomial and establish model knot
Structure such as following formula:
In formula:
L---- gyros export, unit °/h.
L0After ----gyro starts, the zero bias output obtained by sampling in first two minutes, unit °/h.
The quick temperature of T---- gyros, unit DEG C
Δ T---- gyro thermogrades, unit DEG C
DT/dt---- gyro rate of temperature changes, unit DEG C/s
Ai、Bj、Cj----multinomial coefficient,
M, the highest power of each temperature factors of n----.
2nd, the coefficient A in model multinomiali、Bj、CjWith regression analysis least square fitting.Multinomial model is writeable
For:
L-L0=Ta (2)
Wherein:
Q is the exponent number of temperature drift model, and T is optical fibre gyro temperature matrices, and N is gyro temperature drift data amount check.
3rd, the coefficient fitted under different temperatures is different that each coefficient of Ai, Bj, Ck meets following relation in formula (1):
Step 2: choose fitting of a polynomial compensating parameter
1st, in actual use, to each gyro under different temperatures by least-squares calculation, it can obtain coefficient Aij (i
=1,2 ... q;J=0,1,2,3).It is solidificated in the test software of computer.As long as measure gyro after gyro startup to open
Initial temperature T when dynamic0, you can each coefficient in the model is calculated according to formula (3).
2 and then according to each temperature factor, the zero bias of current gyro are estimated using multinomial model formula (1), this is estimated
The zero bias gone out deduct, the zero bias after as compensating.
3rd, in this method, temperature on fiber gyro zero bias are influenceed compensation and compensated using second order or quadravalence, thermograde and temperature
Degree rate of change influences compensation to optical fibre gyro zero bias and uses first compensation phase.Above-mentioned parameter is experiment optimal parameter.
Embodiment:
1st, tested optical fibre gyro is the advanced high-precision optical fiber gyro of certain type, it is desirable to gyro performance indications:Zero bias are steady
Qualitative to be better than 0.02 °/h, scale factor stability is better than 10ppm.
Test hardware condition includes temperature control turntable and auxiliary facility, and concrete configuration is as follows:
(1) temperature control turntable
- 20 DEG C~+60 DEG C of temperature range;Speed output area:0.01 °/s~1000 °/s;Rate stability:1× 10-
4;Temperature stability:±0.5℃.
(2) supporting test facilities
Vibrating isolation foundation, the interference data acquisition device for avoiding external vibration from testing optical fibre gyro, for gyro data
Collection;Turntable control computer, the collection of control, gyro data for turntable.
Fig. 1 is temperature experimental facilities connection figure.2 temperature sensors are located at the top and side of gyro housing respectively, use
In record environment temperature.Gyro gathers the output of gyro and the temperature value of temperature sensor after starting, sample frequency is adopted to be per second
Sample 1 time.
2nd, in order to examine the temperature characterisitic of optical fibre gyro, the gyro zero of totally 8 fixed temperatures is scheduled according to experimental program
Bias testing.4 experiments are scheduled in each fixed temperature, and wherein certain experimental result is as shown in table 1.
The different fixed temperature gyro zero bias results of table 1
According to the data of table 1, the influence of temperature on fiber gyro zero bias is very big, it is necessary to is modified compensation.
3rd, it is the temperature characterisitic of comprehensive analysis gyro zero bias, using data in table 1, multinomial plan is carried out according to formula (1)
Close and compensate.Fitting result is as shown in Figure 2.
4th, temperature-compensating is up to 4 ranks, and thermograde compensation is 1 rank, rate of temperature change compensation is 1 rank.
(1) influence first to temperature compensates.
The temperature experiment one of table 2 to fourth order polynomial compensation result compares
It was found from table 2 and Fig. 3, the standard deviation of gyro zero bias all diminishes after compensation, and wherein second order polynomial compensation effect is most
It is good.
(2) after increasing the compensation of the rank of thermograde 1 on the basis of temperature-compensating, gyro zero bias standard deviation result is as shown in table 3.
The temperature experiment of table 3 increase thermograde compensation result compares
It was found from table 3 and Fig. 4, the compensation result improvement to same order is more apparent, wherein the second order of increase temperature difference is multinomial
Formula compensation effect is best, and standard deviation is reduced to initial value 2/3.
(3) on the basis of temperature, thermograde is considered, influence of the rate of temperature change to gyro zero bias, gyro are added again
Zero bias standard deviation result is as shown in table 4.
The temperature of table 4, thermograde, rate of temperature change compensation effect compare
It can be seen that from table 4 and Fig. 5 bright by " fourth order polynomial+temperature difference+rate of temperature change is fitted " compensation effect
It is aobvious, gyro zero bias standard deviation can be down to 1/3, the compensation effect of " second order polynomial+temperature difference+rate of temperature change fitting " is same
It is more obvious.
4th, in this method, temperature on fiber gyro zero bias are influenceed compensation and compensated using second order or quadravalence, thermograde and temperature
Degree rate of change influences compensation to optical fibre gyro zero bias and uses first compensation phase.Above-mentioned parameter is experiment optimal parameter..
In addition to the implementation, it is all to use equivalent transformation or equivalent replacement present invention additionally comprises there is other embodiment
The technical scheme that mode is formed, it all should fall within the scope of the hereto appended claims.
Claims (2)
- A kind of 1. raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique, it is characterised in that:Methods described Comprise the following steps:Step 1: establish fitting of a polynomial compensation modelThe influence of temperature on fiber gyro zero bias is mainly manifested in three temperature, rate of temperature change and thermograde aspects,1) temperature drift for gyro is fitted using multinomial establishes model structure such as following formula:<mrow> <mi>L</mi> <mo>=</mo> <msub> <mi>L</mi> <mn>0</mn> </msub> <mo>+</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>A</mi> <mi>i</mi> </msub> <msup> <mi>T</mi> <mi>i</mi> </msup> <mo>+</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>B</mi> <mi>j</mi> </msub> <msup> <mrow> <mo>(</mo> <mfrac> <mrow> <mi>d</mi> <mi>T</mi> </mrow> <mrow> <mi>d</mi> <mi>t</mi> </mrow> </mfrac> <mo>)</mo> </mrow> <mi>j</mi> </msup> <mo>+</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>q</mi> </munderover> <msub> <mi>C</mi> <mi>k</mi> </msub> <msup> <mi>&Delta;T</mi> <mi>k</mi> </msup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>In formula:L---- gyros export, unit °/hL0After ----gyro starts, the zero bias output obtained by sampling in first two minutes, unit °/hThe quick temperature of T---- gyros, unit DEG CΔ T---- gyro thermogrades, unit DEG CDT/dt---- gyro rate of temperature changes, unit DEG C/sAi、Bj、Cj----multinomial coefficientM, the highest power of each temperature factors of n----;2) the coefficient A in model multinomiali、Bj、CjWith regression analysis least square fitting, multinomial model can be written as:L-L0=Ta (2)Wherein:<mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>T</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>T</mi> <mn>1</mn> </msub> </mtd> <mtd> <msubsup> <mi>T</mi> <mn>1</mn> <mn>2</mn> </msubsup> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msubsup> <mi>T</mi> <mn>1</mn> <mi>q</mi> </msubsup> </mtd> </mtr> <mtr> <mtd> <msub> <mi>T</mi> <mn>2</mn> </msub> </mtd> <mtd> <msubsup> <mi>T</mi> <mn>2</mn> <mn>2</mn> </msubsup> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msubsup> <mi>T</mi> <mn>2</mn> <mi>q</mi> </msubsup> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>T</mi> <mi>N</mi> </msub> </mtd> <mtd> <msubsup> <mi>T</mi> <mi>N</mi> <mn>2</mn> </msubsup> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msubsup> <mi>T</mi> <mi>N</mi> <mi>q</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> </mrow> </mtd> <mtd> <mrow> <mi>a</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>a</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>a</mi> <mn>2</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>a</mi> <mi>q</mi> </msub> </mtd> </mtr> </mtable> </mfenced> </mrow> </mtd> </mtr> </mtable> </mfenced>Q is the exponent number of temperature drift model, and T is optical fibre gyro temperature matrices, and N is gyro temperature drift data amount check;3) coefficient fitted under different temperatures is different, and each coefficient of Ai, Bj, Ck meets following relation in formula (1):<mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>A</mi> <mn>10</mn> </msub> <mo>+</mo> <msub> <mi>A</mi> <mn>11</mn> </msub> <msub> <mi>T</mi> <mn>1</mn> </msub> <mo>+</mo> <msub> <mi>A</mi> <mn>12</mn> </msub> <msubsup> <mi>T</mi> <mn>1</mn> <mn>2</mn> </msubsup> <mo>+</mo> <msub> <mi>A</mi> <mn>13</mn> </msub> <msubsup> <mi>T</mi> <mn>1</mn> <mn>3</mn> </msubsup> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <msub> <mi>A</mi> <mn>20</mn> </msub> <mo>+</mo> <msub> <mi>A</mi> <mn>21</mn> </msub> <msub> <mi>T</mi> <mn>2</mn> </msub> <mo>+</mo> <msub> <mi>A</mi> <mn>22</mn> </msub> <msubsup> <mi>T</mi> <mn>2</mn> <mn>2</mn> </msubsup> <mo>+</mo> <msub> <mi>A</mi> <mn>23</mn> </msub> <msubsup> <mi>T</mi> <mn>2</mn> <mn>3</mn> </msubsup> </mrow> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>a</mi> <mi>q</mi> </msub> <mo>=</mo> <msub> <mi>A</mi> <mrow> <mi>q</mi> <mn>0</mn> </mrow> </msub> <mo>+</mo> <msub> <mi>A</mi> <mrow> <mi>q</mi> <mn>1</mn> </mrow> </msub> <msub> <mi>T</mi> <mi>q</mi> </msub> <mo>+</mo> <msub> <mi>A</mi> <mrow> <mi>q</mi> <mn>2</mn> </mrow> </msub> <msubsup> <mi>T</mi> <mi>q</mi> <mn>2</mn> </msubsup> <mo>+</mo> <msub> <mi>A</mi> <mrow> <mi>q</mi> <mn>3</mn> </mrow> </msub> <msubsup> <mi>T</mi> <mi>q</mi> <mn>3</mn> </msubsup> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>Step 2: choose fitting of a polynomial compensating parameter1) in actual use, to each gyro under different temperatures by least-squares calculation, it can obtain coefficient Aij(i=1, 2…q;J=0,1,2,3), it is solidificated in the test software of computer, as long as gyro startup is measured after gyro startup Initial temperature T0, you can each coefficient in the model is calculated according to formula (3);2) and then according to each temperature factor, the zero bias of current gyro is estimated using multinomial model formula (1), this is estimated Zero bias deduct, the zero bias after as compensating.
- 2. a kind of raising optical fibre gyro bias instaility method based on Polynomial Fitting Technique according to claim 1, It is characterized in that:Temperature on fiber gyro zero bias are influenceed compensation and compensated using second order or quadravalence, thermograde and rate of temperature change Compensation is influenceed on optical fibre gyro zero bias and uses first compensation phase.
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