CN109059908B - Method for extracting disturbance information in inertial sensor signal of photoelectric tracking system of moving platform - Google Patents
Method for extracting disturbance information in inertial sensor signal of photoelectric tracking system of moving platform Download PDFInfo
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- CN109059908B CN109059908B CN201810688189.6A CN201810688189A CN109059908B CN 109059908 B CN109059908 B CN 109059908B CN 201810688189 A CN201810688189 A CN 201810688189A CN 109059908 B CN109059908 B CN 109059908B
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Abstract
The invention provides a method for extracting disturbance information in a signal of an inertial sensor of a photoelectric tracking system of a moving platform, which comprises the following steps of 1) acquiring an output aliasing signal of the inertial sensor with the sampling frequency of 2 x fs according to the sampling frequency fs of the signal of the inertial sensor required by the photoelectric tracking system of the moving platform in actual engineering; 2) sampling aliasing signals output by an inertial sensor with the frequency of 2 x fs by adopting a down-sampling method to obtain 2 needed aliasing signals with the frequency of fs; 3) performing characteristic analysis on 2 sampled aliasing signals with frequency fs to determine signal characteristics; 4) and (3) taking 2 signals with frequency fs as observation signals, and separating aliasing signals output by the inertial sensor by using a blind source separation algorithm to obtain disturbance signals in the aliasing signals. The method can accurately extract the disturbance signal in the aliasing signal output by the inertial sensor, has the advantages of simplicity, high calculation speed and strong real-time property, avoids manual experience setting in the disturbance signal extraction process, and has strong self-adaptability.
Description
Technical Field
The invention belongs to the field of digital signal processing, and particularly relates to a method for extracting disturbance information in an inertial sensor signal of a photoelectric tracking system of a motion platform.
Background
In the photoelectric tracking system of the moving platform, the motion of a carrier and the interference of the external environment on the carrier can be coupled to the tracking platform to cause the visual axis to shake, so that the visual axis deviates from a tracking target, and the tracking performance is reduced. Therefore, the system usually adopts an inertial stabilization platform to control the disturbance of the system, so as to ensure the stability of the visual axis of the system, and because the stabilization control needs a disturbance signal as a feedforward control signal, the system disturbance decoupling is realized by using the photoelectric stabilization control of a motion carrier, and the disturbance information in the aliasing signal output by the inertial sensor of the system must be extracted.
How to extract disturbance information in an inertial sensor signal in a moving carrier photoelectric system, currently, a signal filtering method is mostly adopted, a low-frequency target signal in an aliasing signal is filtered, and then a difference is made between the filtered signal and an original aliasing signal to obtain a disturbance signal in the aliasing signal, wherein the commonly used filtering method comprises the following steps: IIR filtering, wavelet filtering and Kalman filtering. However, the above method may have too many decisions in the filtering process by using signal prior knowledge and human experience. The IIR filtering method needs to know the specific frequencies of different signals contained in the aliasing signals in advance, and artificially designs the pass band of the filter, so that unreasonable design of the pass band width has great influence on the filtering result. The wavelet filtering method needs to select a threshold function, a wavelet basis function and a decomposition layer number for a low-frequency band target signal in the signal, and a filtering result has a large error due to improper selection of the threshold function and the wavelet basis function. Kalman filtering needs to establish an accurate mathematical model of disturbance signals, the output aliasing signals of the fiber-optic gyroscope are complex, the accurate model of disturbance sources is difficult to obtain, and the result of Kalman filtering is inaccurate due to inaccurate model estimation. The methods can extract disturbance information in aliasing signals output by the inertial sensor of the photoelectric tracking system of the motion platform to a certain extent, but artificial parameters are set too much, requirements on signal priori knowledge are strict, the filtering process is complex, and engineering implementation is not facilitated.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method can be self-adaptive and can quickly realize the extraction of disturbance information in the signal of the inertial sensor of the photoelectric tracking system of the moving platform under the condition of not depending on signal prior knowledge and artificial experience setting.
The technical scheme of the invention is as follows: a method for extracting disturbance information in a signal of an inertial sensor of a photoelectric tracking system of a moving platform comprises the following specific steps:
the method comprises the following steps that (1) according to the signal sampling frequency fs of an inertial sensor required by a photoelectric tracking system of a motion platform in actual engineering, aliasing signals output by the inertial sensor with the sampling frequency of 2 x fs are obtained;
sampling the aliasing signals output by the inertial sensor with the frequency of 2 x fs by adopting a down-sampling method, wherein the sampling factor is 2, and the sampling period is changed into 2 times of the original sampling period, so that the required 2 aliasing signals with the frequency of fs can be obtained;
step (3) performing characteristic analysis on 2 sampled aliasing signals with frequency fs to determine signal characteristics;
the blind source separation in step (4) may be expressed AS a matrix X ═ AS, where s is the unknown n source signals, a is the m × n mixing matrix, and X is the m observed signals received by the sensor. Typically, the source signal and the observed signal have the same dimension, i.e., A is full rankMatrix (A)-1A ═ I), the objective of blind source separation is to find the inverse matrix estimate of a
Thereby obtaining an estimate of the source signal S
Namely, it is
And taking 2 signals with frequency fs as observation signals, and selecting a blind source separation algorithm to perform self-adaptive separation on aliasing signals output by the inertial sensor, so as to extract disturbance information in the aliasing signals.
The signal characteristic analysis in the step (3) adopts signal spectrum analysis.
The blind source separation algorithm adopted in the step (4) may be a FastICA algorithm.
The invention has the advantages that:
(1) the invention obtains 2 observation signals by a down-sampling method, realizes the conversion from a single-channel signal to a multi-channel signal, and can realize the extraction of disturbance information in the signal of the inertial sensor of the photoelectric tracking system without adding an additional sensor.
(2) Compared with the traditional filtering mode, the method for extracting the interference signal in the inertial sensor signal of the photoelectric tracking system provided by the invention can be used for extracting the high-frequency-band interference signal in the aliasing signal without manually setting filtering parameters, so that the dependence on signal priori knowledge in the filtering process and the error caused by manual experience setting are avoided, and the adaptability is strong.
(3) The method has the advantages of simple algorithm, high calculation speed, strong real-time performance and convenience for engineering application.
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FIG. 1 shows an output aliasing signal of an inertial sensor of a photoelectric tracking system with a sampling frequency of 2 xfs according to the present invention;
fig. 2 is a diagram showing a result of sampling an aliasing signal output by an inertial sensor of a photoelectric tracking system with a frequency of 2 xfs by using a down-sampling method according to the present invention, where fig. 2(a) shows 2 aliasing signals with a frequency of fs obtained by down-sampling, and fig. 2(b) shows a spectrum diagram corresponding to the signal in fig. 2 (a);
fig. 3 is a diagram of a result of extracting disturbance information from an inertial sensor signal of a photoelectric tracking system obtained by the method of the present invention, where fig. 3(a) is a target signal and a disturbance signal obtained by the method of the present invention, and fig. 3(b) is a graph of a spectrum corresponding to the signal in fig. 3 (a);
FIG. 4 is a flowchart of a method for extracting disturbance information from an inertial sensor signal of a photoelectric tracking system of a moving platform according to the present invention.
Detailed Description
Embodiments of the present invention are described below with reference to the drawings. However, the following examples are only illustrative of the present invention.
As shown in fig. 4, the method for extracting disturbance information from inertial sensor signals of a photoelectric tracking system of a moving platform according to the present invention specifically comprises the following steps:
the method comprises the following steps that (1) according to the signal sampling frequency fs of an inertial sensor required by a photoelectric tracking system of a motion platform in actual engineering, aliasing signals output by the inertial sensor with the sampling frequency of 2 x fs are obtained;
sampling the aliasing signals output by the inertial sensor with the frequency of 2 x fs by adopting a down-sampling method, wherein the sampling factor is 2, and the sampling period is changed into 2 times of the original sampling period, so that the required 2 aliasing signals with the frequency of fs can be obtained;
step (3) performing characteristic analysis on 2 sampled aliasing signals with frequency fs to determine signal characteristics;
the signal characteristic analysis in the step (3) adopts signal spectrum analysis.
The blind source separation in step (4) may be expressed AS a matrix X ═ AS, where S is the unknown n source signals, a is the m × n mixing matrix, and X is the m observed signals received by the sensor. Typically, the source signal and the observed signal have the same dimension, i.e., A is a full rank matrix (A)-1A ═ I), the objective of blind source separation is to find the inverse matrix estimate of a
Thereby obtaining an estimate of the source signal S
Namely, it is
And taking 2 signals with frequency fs as observation signals, and selecting a blind source separation algorithm to perform self-adaptive separation on aliasing signals output by the inertial sensor, so as to extract disturbance information in the aliasing signals.
The blind source separation algorithm adopted in the step (4) may be a FastICA algorithm.
Next, an example of an output signal of an inertial sensor (fiber optic gyro) in a photoelectric tracking system under a ship-mounted condition will be described. The method comprises the following specific implementation steps:
(1) in actual engineering, the sampling frequency of a fiber optic gyroscope signal required by a photoelectric tracking system is 100 Hz, and a fiber optic gyroscope output aliasing signal with the sampling frequency of 200 Hz is obtained, as shown in FIG. 1;
(2) sampling the aliasing signals output by the fiber optic gyroscope with the frequency of 200 Hz by adopting a down-sampling method to obtain 2 aliasing signals with the frequency of 100 Hz, as shown in FIG. 2 (a);
(3) the sampled 2 aliased signals with frequency of 100 hz are subjected to spectral analysis, as shown in fig. 2 (b). As can be seen from the figure, the output aliasing signal of the fiber-optic gyroscope mainly consists of a low-frequency target angular velocity signal of about 0.01 Hz and a high-frequency disturbing signal of about 33 Hz in the shipborne background.
(4) 2 aliasing signals with the frequency of 100 Hz in FIG. 2(a) are used as observation signals, and a target angular velocity signal and a disturbing signal in the aliasing signals are obtained by separation by using a FastICA algorithm, as shown in FIG. 3(a), a separation signal 1 in the figure is a target angular velocity signal, and a separation signal 2 is a disturbing signal. The target angular velocity signal and the interference signal in fig. 3(a) are subjected to spectrum analysis, and the result is shown in fig. 3(b), and it can be seen from the figure that the frequency spectrums of the separation signal 1 and the separation signal 2 are not mixed, which indicates that the frequency spectrums of the low-frequency target signal of about 0.1 hz and the high-frequency-band disturbance signal of about 33 hz obtained by the method are not mixed, that is, the method of the invention realizes the extraction of disturbance information in the output mixed signal of the fiber-optic gyroscope of the optoelectronic system of the motion platform, and the extracted disturbance information is shown as the separation signal 2 in fig. 3 (a).
Claims (3)
1. A method for extracting disturbance information in a signal of an inertial sensor of a photoelectric tracking system of a moving platform is characterized by comprising the following steps:
the method comprises the following steps that (1) according to the signal sampling frequency fs of an inertial sensor required by a photoelectric tracking system of a motion platform in actual engineering, aliasing signals output by the inertial sensor with the sampling frequency of 2 x fs are obtained;
sampling aliasing signals output by an inertial sensor with the frequency of 2 x fs by adopting a down-sampling method, wherein the sampling factor is 2, and the sampling period is changed into 2 times of the original sampling period, so that the required 2 aliasing signals with the frequency of fs can be obtained;
step (3), performing characteristic analysis on 2 sampled aliasing signals with frequency fs to determine signal characteristics;
in step (4), blind source separation may be expressed AS a matrix X ═ AS, where s is unknown n source signals, a is a mixed matrix of m × n, and X is m observation signals received by the sensor, and in general, the source signals and the observation signals have the same dimension, that is, a is a full rank matrix, that is, a-1I, the objective of blind source separation is to find the inverse matrix estimate W of a,
thereby obtaining an estimate of the source signal s
Namely, it is
And taking 2 signals with frequency fs as observation signals, and selecting a blind source separation algorithm to perform self-adaptive separation on aliasing signals output by the inertial sensor, so as to extract interference signals in the aliasing signals.
2. The method for extracting disturbance information in the signal of the inertial sensor of the photoelectric tracking system of the moving platform according to claim 1, wherein the method comprises the following steps: the signal characteristic analysis in the step (3) adopts signal spectrum analysis.
3. The method for extracting disturbance information in the signal of the inertial sensor of the photoelectric tracking system of the moving platform according to claim 1, wherein the method comprises the following steps: the blind source separation algorithm adopted in the step (4) may be a FastICA algorithm.
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