CN115824198A - Method for selecting and switching optical gyroscope cold and hot start temperature error compensation model - Google Patents
Method for selecting and switching optical gyroscope cold and hot start temperature error compensation model Download PDFInfo
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Abstract
The invention provides a method for selecting and switching an optical gyro cold and hot start temperature error compensation model, which obtains the temperature space gradient among different positions of a gyro at the moment of starting the inertial navigation through a plurality of temperature sensors distributed in a gyro instrument area in the inertial navigation. The inertial navigation 'cold start' and 'hot start' are considered as two populations, and the 'mahalanobis distance' from the sample set formed by the spatial gradient to the two populations is calculated. The method can judge the temperature state of inertial navigation in a very short time when the inertial navigation is started, select a correct error model to compensate the output of the gyroscope, can complete the transition switching of the compensation model when the gyroscope enters a hot-state long-time stable working stage from a cold-state starting stage, and is compatible with different working states of cold-state starting and hot-state starting. The method has the advantages of small calculated amount, simplicity, practicability and convenience for engineering realization.
Description
Technical Field
The application relates to the technical field of inertial navigation, in particular to a method for selecting and switching an optical gyroscope cold and hot start temperature error compensation model.
Background
The optical gyroscope mainly comprises an optical fiber gyroscope and a laser gyroscope, has the outstanding advantages of wide angular velocity measurement range, overload impact resistance, short starting time and the like compared with a classical rotor gyroscope, and is particularly suitable for a strapdown inertial navigation system. As a core instrument of the inertial navigation system, the performance of a gyroscope directly determines the navigation precision of the inertial navigation system. However, the output of the optical gyro is affected by temperature, and the generated instrument temperature error seriously restricts the improvement of system alignment, navigation precision and quick response performance. The solution commonly adopted at present is temperature error compensation. Temperature error compensation is essentially a mathematical modeling based method that is excited by a temperature test and separates the temperature error from the gyro output, and models the error and temperature using their correlation and deducts them from the system output. However, in the specific implementation process, the temperature error behavior mode of the gyro is greatly different under two conditions of starting from a cold environment (the gyro is powered off and cooled for a long time before the start and is approximately in thermal balance with the environment) and starting from a hot environment (the gyro is powered on for a long time before the start and the internal temperature is higher than the ambient temperature).
The gyro temperature error model obtained through a long-time full-temperature range temperature test is basically a hot-state model, and cannot accurately describe the error mode in the cold-state starting stage of the starting, so that the targeted modeling needs to be carried out on the short process of the cold-state starting of the gyro. The gyro temperature error models established under the two conditions cannot be used universally, so that the temperature state of inertial navigation needs to be accurately judged in a very short time when the inertial navigation is started, so that the correct error model can be selected to compensate gyro output, and the model transition switching from a cold-state starting stage to a hot-state long-time stable working stage of the gyro can be completed.
At present, most of public researches are focused on gyro temperature error compensation in a long-time working stage of inertial navigation, the attention on the gyro cold-state starting condition is less, and a selection and switching method of cold and hot starting models for different working stages is hardly involved.
Disclosure of Invention
In order to solve the technical problem, the invention provides a method for selecting and switching an optical gyroscope cold and hot start temperature error compensation model. The technical scheme adopted by the invention is as follows:
a method for selecting and switching an optical gyroscope cold and hot start temperature error compensation model comprises the following steps:
step 1, distributing a plurality of temperature sensors at different positions of different gyros of inertial navigation, and setting the total distribution number to be n;
step 2, calculating the temperature space gradient by using the absolute temperature difference values measured by the temperature sensors at different positions;
step 3, respectively carrying out n 1 Group inertial navigation cold environment starting test and n 2 Taking the group inertial navigation hot-state starting test as a training data set, taking two environments of a cold state and a hot state as two universes, and recording the universes as G 1 And G 2 (ii) a Calculating estimates of ensemble mean of temperature gradients of two ensembles separately
And covariance estimation
Step 4, judging cold state and hot state starting based on a judgment threshold TSH according to the Mahalanobis distance overall judgment criterion;
step 5, if the hot start is judged through the step 4, directly selecting a hot start temperature error compensation model Mod 2 Compensating gyro output, mod 2 The error compensation amount calculated in real time for the pre-established thermal state temperature error model can be expressed as
Wherein T is g (t)＝[T g1 (t)T g2 (t)...T gn (t)] T Is the real-time temperature collected by the gyro temperature sensor,
a thermal state temperature error compensation quantity function established according to the correlation between the error and the temperature;
if the cold start is judged through the step 4, the inertial navigation working time t is less than t G Internal cold-state starting temperature error compensation model Mod 1 Compensating gyro output, mod 1 The error compensation amount calculated in real time for the pre-established cold state temperature error model can be expressed as
Representing a cold temperature error compensation quantity function, t, established on the basis of the error-temperature dependence G The applicable duration of the model is started in a cold state; at t G ≤t≤t T Internal arrangement of the transition process, t T For the arranged model transition duration, smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using a transition function; when t is>t T Then, a thermal state starting temperature error compensation model Mod is adopted 2 And compensating the output of the gyroscope.
Further, in step 1, the disposing a plurality of temperature sensors at different positions of different gyros in inertial navigation includes:
1 temperature sensor is respectively arranged on the gyroscope in the X, Y, Z three directions, namely n =3; or
For the laser gyroscope, a temperature sensor is respectively arranged on each gyroscope anode and the shell, namely n =6; or
For the fiber-optic gyroscope, a temperature sensor is respectively arranged at the position of each gyroscope close to the optical fiber and close to the surface of the shell, namely n =6.
Further, in step 2, the calculating the temperature spatial gradient includes:
let the real-time temperature measurement values of n temperature sensors be T gi (t), i =1, …, n, the temperature gradient between the two temperature sensors is expressed as:
through the above calculation formula, the maximum value is obtained by calculation
A spatial gradient of temperature.
Further, in step 2, after the calculating the temperature spatial gradient, the method further includes:
according to the actual situation, the calculation results
K of the temperature space gradients are selected
Typical gradient composition measurement sample Δ T g (T), the measurement sample Δ T g (t) is expressed as:
recording inertial navigation starting time T =0 and corresponding to temperature gradient delta T g (T) smoothing to obtain a temperature gradient smoothing value Delta T gs Let the smoothing time be Δ t, expressed as:
the value Δ t =1s since the absolute temperature noise is small.
Further, the estimation of the ensemble mean of the temperature gradients of the two ensembles is calculated separately
And
the method comprises the following steps:
smoothing the value Δ T according to the test results and the temperature gradient gs Under the two population conditions, the temperature gradient elements belonging to the two populations are respectively expressed as
Estimation of the ensemble mean of the temperature gradients of two ensembles
And
calculated by the following formula:
further, the covariance estimation
Calculated by the following formula:
further, the discrimination threshold TSH is expressed as
Wherein the content of the first and second substances,
further, in step 4, the determining cold and hot starts based on the determination threshold TSH includes:
real-time temperature space gradient delta T obtained by using the discrimination threshold value to inertial navigation starting time gs Performing on-line discrimination if the function omega (delta T) gs )：
ω(ΔT gs )＝a T ·ΔT gs ≥TSH
Judging that the inertial navigation is in a cold starting state; otherwise, judging that the inertial navigation is in a hot starting state.
Further, the smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using the transition function includes:
at t G ≤t≤t T Simultaneous cold state model Mod calculation in time period 1 And thermal state model Mod 2 Real-time compensation amount Δ M 1 (t) and Δ M 2 (t); smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using a transition function F (t), wherein the compensation quantity is represented as follows:
ΔM(t)＝[1-F(t)]ΔM 1 (t)+F(t)ΔM 2 (t)t G ≤t≤t T
f (t) is a transition function, and delta M (t) is a transition process temperature error compensation quantity fusing a cold state model and a hot state model.
Further, in step 5, t G And t T The selection needs to be carried out according to the duration of the modeling data set of the cold-state starting model of the inertial navigation system and the temperature characteristic of the inertial navigation.
Through the embodiment of the application, the following technical effects can be obtained:
(1) The method can accurately judge the cold state and the hot state starting of the inertial navigation in a very short time when the inertial navigation is started, select a correct error model to compensate the output of the gyroscope, can complete the natural smooth switching of the compensation model from the cold state starting to the hot state stable working stage of the gyroscope, and is compatible with different working states of the cold state starting and the hot state starting.
(2) The method adopts the spatial gradient distributed in the gyro temperature field as the distinguishing mark of the cold and hot states, does not need to calculate the temperature time change rate, and avoids the influence of noise introduced by obtaining the first-order derivative of the temperature on the judgment accuracy and the starting delay introduced by smooth differential noise.
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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 some embodiments of the present application, and those skilled in the art can also obtain other drawings according to the drawings without inventive labor.
FIG. 1 is a schematic diagram of a temperature error compensation model selection and switching process according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
FIG. 1 is a schematic diagram of a temperature error compensation model selection and switching process according to the present invention. The technology of the invention solves the problem that the temperature space gradient between different positions of the gyroscope at the starting moment of inertial navigation is obtained by a plurality of temperature sensors distributed in a gyroscope instrument area in the inertial navigation. The inertial navigation "cold start" and "hot start" are considered as two populations, and the mahalanobis distance of the set of samples formed by the spatial gradient to the two populations is calculated. The method comprises the steps of training cold-state starting and hot-state starting temperature tests in advance for multiple times to generate a distance discrimination threshold value, taking the distance discrimination threshold value as a discrimination basis for cold-state and hot-state starting, carrying out online discrimination on a temperature space gradient obtained at the moment of inertial navigation starting by using the criterion, and directly selecting a hot-state starting temperature error compensation model to compensate gyro output if the judgment result is that the gyro is hot-state starting; if the starting is judged to be cold, the working time t of inertial navigation is less than t G Compensating the gyro output by using a cold start temperature error compensation model internally (t) G The applicable duration of the cold start model). Then, at t G ≤t≤t T Arranging the transition process inside (t) T For a scheduled model transition duration), smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using a transition function. When t is>t T And then, compensating the output of the gyroscope by adopting a thermal state starting temperature error compensation model. The method for selecting and switching the optical gyro cold and hot start temperature error compensation model based on spatial gradient discrimination utilizes the temperature spatial gradient measured by different gyro temperature sensors to calculate the Mahalanobis distance so as to realize accurate discrimination of inertial navigation cold state and hot state start, and arranges a transition process to realize natural switching of cold state and hot state models, as shown in FIG. 1.
The temperature error compensation model selecting and switching method comprises the following steps:
step 1, distributing a plurality of temperature sensors at different positions of different gyros of inertial navigation, and setting the total distribution number to be n.
In step 1, the arranging a plurality of temperature sensors at different positions of different gyros of inertial navigation includes:
1 temperature sensor is respectively arranged on the gyroscope in the X, Y, Z three directions, namely n =3;
for the laser gyroscope, a temperature sensor is respectively arranged on each gyroscope anode and the shell, namely n =6;
for the fiber-optic gyroscope, a temperature sensor is respectively arranged at the position of each gyroscope close to the optical fiber and close to the surface of the shell, namely n =6;
step 2, calculating the temperature space gradient by using the absolute temperature difference values measured by the temperature sensors at different positions;
in step 2, the calculating the temperature spatial gradient includes:
let the real-time temperature measurement values of n temperature sensors be T gi (t), i =1, …, n, the temperature gradient between the two temperature sensors is expressed as:
through the above calculation formula, the maximum value is obtained by calculation
A temperature spatial gradient;
in step 2, the calculating the temperature spatial gradient further comprises:
according to the actual situation, obtained from said calculation
K of the temperature space gradients are selected
Typical gradient composition measurement sample Δ T g (T), the measurement sample Δ T g (t) is expressed as:
recording inertial navigation starting time T =0 and corresponding to temperature gradient delta T g (T) smoothing to obtain a temperature gradient smoothing value Delta T gs Let the smoothing time be Δ t, expressed as:
the value Δ t =1s because the absolute temperature noise is small;
step 3, respectively carrying out n 1 Group inertial navigation cold environment starting test and n 2 Taking the group inertial navigation hot-state starting test as a training data set, taking two environments of a cold state and a hot state as two universes, and recording the universes as G 1 And G 2 (ii) a Calculating estimates of the mean of two populations of temperature gradients
And covariance estimation
The estimation of the ensemble mean of the temperature gradients of the two ensembles is calculated separately
And
the method comprises the following steps:
smoothing the value Δ T according to the test results and the temperature gradient gs Under the two population conditions, the temperature gradient elements belonging to the two populations are respectively expressed as
Estimation of the ensemble mean of the temperature gradients of two ensembles
And
calculated by the following formula:
the covariance estimate
Calculated by the following formula:
step 4, judging cold state and hot state starting based on a judgment threshold TSH according to the Mahalanobis distance overall judgment criterion;
the discrimination threshold TSH is expressed as
Wherein the content of the first and second substances,
in step 4, the cold state and the hot state start are determined based on the determination threshold TSH, and the method includes:
real-time temperature space gradient delta T obtained by using the discrimination threshold value to inertial navigation starting time gs Performing on-line discrimination, if the function omega (delta T) is discriminated gs )：
ω(ΔT gs )＝a T ·ΔT gs ≥TSH
Judging that the inertial navigation is in a cold starting state; otherwise, judging that the inertial navigation is in a hot starting state;
step 5, if the hot start is judged through the step 4, directly selecting a hot start temperature error compensation model Mod 2 Compensating gyro output, mod 2 The error compensation amount calculated in real time for the pre-established thermal state temperature error model can be expressed as
Wherein T is g (t)＝[T g1 (t)T g2 (t)...T gn (t)] T Is the real-time temperature collected by the gyro temperature sensor,
in order to establish a thermal state temperature error compensation quantity function according to the correlation between the error and the temperature, a polynomial can be specifically adopted for modeling: for example, if a single temperature sensor is used,
can be expressed as
(a 0 ，a 1 ，a 2 As model coefficients);
if the cold start is judged through the step 4, the inertial navigation working time t is less than t G Compensating the gyro output by using a cold start temperature error compensation model internally, t G The applicable duration of the model is started in a cold state; at t G ≤t≤t T Arranging the transition process in, t T For the arranged model transition duration, smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using a transition function; when t is>t T And then, compensating the output of the gyroscope by adopting a thermal state starting temperature error compensation model.
The compensating the gyro output by using the cold-start temperature error compensation model comprises the following steps: using cold start temperature error compensation model Mod 1 Compensating gyro output, mod 1 The error compensation amount calculated in real time for the pre-established cold state temperature error model can be expressed as
The function of the cold-state temperature error compensation quantity established according to the correlation between the error and the temperature is shown, and a polynomial can be used for modeling: if a single temperature measuring sensor is used,
can be expressed as
(b 0 ，b 1 ，b 2 As model coefficients).
The step of smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using the transition function comprises the following steps:
at t G ≤t≤t T Simultaneous cold state model Mod calculation in time period 1 With thermal state model Mod 2 Real-time compensation amount Δ M 1 (t) and Δ M 2 (t); using transitionsThe function F (t) smoothly and gradually switches the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model, and is represented as:
ΔM(t)＝[1-F(t)]ΔM 1 (t)+F(t)ΔM 2 (t)t G ≤t≤t T
f (t) is a transition function, and delta M (t) is a transition process temperature error compensation quantity fusing a cold state model and a hot state model;
the adoption hot-state starts temperature error compensation model and compensates gyro output includes: adopt hot-state start-up temperature error compensation model Mod 2 And compensating the output of the gyroscope.
In the concrete implementation process, t G And t T The selection needs to be carried out according to the duration of the modeling data set of the cold-state starting model of the inertial navigation system and the temperature characteristic of the inertial navigation.
By adopting the scheme, the method can accurately judge the cold state and the hot state starting of the inertial navigation in a very short time when the inertial navigation is started, select a correct error model to compensate the output of the gyroscope, can complete the natural smooth switching of the compensation model from the cold state starting to the hot state stable working stage of the gyroscope, and is compatible with different working states of the cold state starting and the hot state starting.
The functions described above in this application may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a load programmable logic device (CPLD), and the like.
Further, while operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or logical acts of devices, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (10)
1. A method for selecting and switching an optical gyro cold and hot start temperature error compensation model is characterized by comprising the following steps:
step 1, distributing a plurality of temperature sensors at different positions of different gyros of inertial navigation, and setting the total distribution number to be n;
step 2, calculating a temperature space gradient by using absolute temperature differences measured by temperature sensors at different positions;
step 3, respectively carrying out n 1 Group inertial navigation cold environment starting test and n 2 Taking the group inertial navigation hot-state starting test as a training data set, taking two environments of a cold state and a hot state as two universes, and recording the universes as G 1 And G 2 (ii) a Calculating estimates of the mean of two populations of temperature gradients
And covariance estimation
Step 4, judging cold state and hot state starting based on a judgment threshold TSH according to the Mahalanobis distance overall judgment criterion;
step 5, if the hot start is judged through the step 4, directly selecting a hot start temperature error compensation model Mod 2 Compensating gyro output, mod 2 The error compensation amount calculated in real time for the pre-established thermal state temperature error model can be expressed as
Wherein T is g (t)＝[T g1 (t) T g2 (t) ... T gn (t)] T Is the real-time temperature collected by the gyro temperature sensor,
a thermal state temperature error compensation quantity function established according to the correlation between the error and the temperature;
if the cold start is judged through the step 4, the inertial navigation working time t is less than t G Internal-use cold-start temperature error compensation model Mod 1 Compensating gyro output, mod 1 The error compensation obtained in real time for the pre-established cold state temperature error model can be expressed as
Representing a cold temperature error compensation function, t, based on the error-temperature dependence G The applicable duration of the model is started in a cold state; at t G ≤t≤t T Arranging the transition process in, t T For the arranged model transition duration, smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using a transition function; when t is>t T Then, a hot-state starting temperature error compensation model Mod is adopted 2 And compensating the output of the gyroscope.
2. The method of claim 1, wherein in step 1, the disposing a plurality of temperature sensors at different positions of different gyros of inertial navigation comprises:
1 temperature sensor is respectively arranged on the gyroscope in X, Y, Z three directions, namely n =3 at the moment; or
For the laser gyroscope, a temperature sensor is respectively arranged on each gyroscope anode and the shell, namely n =6; or alternatively
For the fiber-optic gyroscope, a temperature sensor is respectively arranged at the position of each gyroscope close to the optical fiber and close to the surface of the shell, namely n =6.
3. The method of claim 1, wherein in step 2, said calculating a temperature spatial gradient comprises:
let the real-time temperature measurement values of n temperature sensors be T gi (t), i =1, …, n, the temperature gradient between the two temperature sensors is expressed as:
through the above calculation formula, the maximum value is obtained by calculation
A spatial gradient of temperature.
4. The method of claim 3, wherein in step 2, the calculating the temperature spatial gradient further comprises:
according to the actual situation, the calculation results
K of the temperature space gradients are selected
Typical gradient composition measurement sample Δ T g (T), the measurement sample Δ T g (t) is expressed as:
recording inertial navigation starting time T =0 and corresponding to temperature gradient delta T g (T) smoothing to obtain a temperature gradient smoothing value Delta T gs Let the smoothing time be Δ t, expressed as:
the value Δ t =1s since the absolute temperature noise is small.
5. The method of claim 1, wherein the separately calculating estimates of the ensemble mean of the temperature gradients of the two ensembles
And
the method comprises the following steps:
smoothing the value Δ T according to the test results and the temperature gradient gs Under the two population conditions, the temperature gradient elements belonging to the two populations are respectively expressed as
Estimation of the ensemble mean of the temperature gradients of two ensembles
And
calculated by the following formula:
6. the method of claim 5, wherein the covariance estimate
Calculated by the following formula:
7. the method according to claim 1, characterized in that said discrimination threshold TSH is expressed as
Wherein the content of the first and second substances,
8. the method according to one of claims 1 or 7, wherein determining cold and hot starts based on a discrimination threshold TSH in step 4 comprises:
real-time temperature space gradient delta T obtained by using the discrimination threshold value to inertial navigation starting time gs Performing on-line discrimination, if the function omega (delta T) is discriminated gs )：
ω(ΔT gs )＝a T ·ΔT gs ≥TSH
Judging that the inertial navigation is in a cold starting state; otherwise, judging that the inertial navigation is in a hot starting state.
9. The method of claim 1, wherein smoothly and gradually switching the compensation amount output by the cold start temperature error compensation model to the compensation amount output by the hot start model by using a transition function comprises:
at t G ≤t≤t T Method for simultaneously calculating cold state model Mod in time period 1 And thermal state model Mod 2 Real-time compensation amount Δ M 1 (t) and; smoothly and gradually switching the compensation quantity output by the cold-state starting temperature error compensation model to the compensation quantity output by the hot-state starting model by using a transition function F (t), wherein the compensation quantity is represented as follows:
ΔM(t)＝[1-F(t)]ΔM 1 (t)+F(t)ΔM 2 (t) t G ≤t≤t T
f (t) is a transition function, and delta M (t) is a transition process temperature error compensation quantity fusing a cold state model and a hot state model.
10. Method according to claim 9, characterized in that in step 5, t is G And t T And selecting according to the duration of a cold-state starting model modeling data set of the inertial navigation system and the temperature characteristic of the inertial navigation.
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