CN105865505B - KID detector array S21 baseline calibration methods based on Kalman filtering - Google Patents
KID detector array S21 baseline calibration methods based on Kalman filtering Download PDFInfo
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Abstract
The KID detector array S21 baseline calibration methods based on Kalman filtering that the invention discloses a kind of, which is characterized in that include the following steps：Step 1：Adaptive-filtering is carried out to KID detector array S21 data using Kalman filtering, obtains the gradual S21 baselines with low frequency characteristic；Step 2：Original S21 data are compared with filtered gradual S21 baselines, realize the baseline calibration of KID detector arrays S21.The KID detector array S21 baseline calibration methods based on Kalman filtering of the present invention have many advantages, such as simple, flexible, and it can disposably complete KID detector array baseline calibrations, it obtains consistency and preferably calibrates effect, be suitable for the S21 baseline calibrations of extensive KID detector arrays different situations.
Description
Technical field
The KID detector array S21 baseline calibration methods based on Kalman filtering that the present invention relates to a kind of, and in particular to one
Kind is used for Terahertz superconduction KID detector array S21 baseline calibration methods based on Kalman filtering, and the invention belongs to Terahertzs
Technical field of research.
Background technology
Terahertz superconduction KID (Kinetic Inductance Detector) detector array is a kind of novel terahertz
Hereby highly-sensitive detector can be used for the detection of the target imagings such as Terahertz frequency range astronomy.It is ground carrying out KID detector array characteristics
In studying carefully, it is a kind of common research means to measure KID detector array transmission characteristic S21 parameters.From KID detector arrays S21
Measurement data in, its resonance-characteristic frequency and quality factor q value information can be obtained, thus further appreciate that its resonator
Temperature become characteristic, noise characteristic of detector etc..
Due to reading circuit system all parts such as cryogenic low noise amplifier, ambient temperature amplifier and filter depositing for intrinsic frequency response
And all parts between Signal Matching, it is uneven to result in KID detector array transmission characteristic S21 baselines jointly, performance
For the integral inclined of baseline or phenomena such as periodically or non-periodically rise and fall, the presence of these disturbing factors will result in KID
The characteristic frequency and Q factor parameter testing precision of detector array reduce.Therefore, KID detector arrays transmission characteristic S21 bases
Line accurate calibration is the key that realize that KID detector array characteristics correctly characterize a ring.
KID detector array transmission characteristic S21 baseline accurate calibrations, the method for use have it is following several, one is utilizing
S21 transmission characteristics at a temperature of KID detector array different operatings are compared to realize its baseline calibration, the master of this method
It is to work as to be operated in shake (off-resonance) in detuning higher than the KID detectors resonance characteristic of critical temperature Tc to want principle
State as reference by the S21 data tested this moment is visited with the KID under actual work temperature (being typically less than critical-temperature)
It surveys device S21 test datas to be compared, to realize KID detector array S21 transmission characteristic baseline calibrations, this method Main Basiss
It is to think that S21 baselines remain unchanged at a temperature of two kinds, i.e., the S21 baselines of detuning state and working condition do not change.To the greatest extent
Pipe can disposably realize the calibration of KID detector array transmission characteristic S21 baselines using this method, but due to different temperatures
When, KID detector array S21 baselines in its operating frequency range often big rise and fall and with frequency variation be difficult to tend to one
It causes, is accordingly difficult to obtain the accurate calibration of full frequency band baseline calibration, or even the situation of baseline calibration mistake occur.
The second is using the KID detector S21 transmission characteristic baseline calibration methods of first-order linear or fitting of a polynomial, due to
Baselines of the KID detector array transmission characteristic S21 near its resonant frequency is from local investigation, often it can be found that its baseline table
It is now the mathematical model relationship of first-order linear or second order polynomial.Therefore KID detector arrays can be carried out roughly using the method
The calibration of row transmission characteristic S21.The shortcomings that calibration method, is more apparent, is mainly manifested in：It is visited by the single KID of linear fit
When surveying device S21 transmission characteristic baseline calibrations, when KID detector S21 characteristics are there are asymmetry or near resonant frequency
Both wings are there are when larger inclination (i.e. uneven), and this method is while being calibrated out S21 baselines, also by the portion containing intrinsic propesties
Point physical message (representing detector circuit parameter, the information such as signal coupling condition) is excessively calibrated.In addition this method is used
The S21 characteristics baseline of KID detector arrays need to be calibrated one by one, data calibration amount increases as array increases on a large scale
Add, is not suitable for extensive KID detector arrays S21 baseline calibrations.
Invention content
To solve the deficiencies in the prior art, the purpose of the present invention is to provide one kind, and based on Kalman filtering, (Kalman is filtered
Wave) KID detector array S21 baseline calibration methods, be difficult to obtain the accurate of full frequency band baseline calibration to solve the prior art
Calibration, or even there is baseline calibration mistake, or excessively calibrated, data calibration amount increases as array increases on a large scale
The technical issues of adding, being not suitable for extensive KID detector arrays S21 baseline calibrations.
In order to realize that above-mentioned target, the present invention adopt the following technical scheme that：
KID detector array S21 baseline calibration methods based on Kalman filtering, which is characterized in that include the following steps：
Step 1：Adaptive-filtering is carried out to KID detector array S21 data using Kalman filtering, is obtained with low
The gradual S21 baselines of frequency characteristic；
Step 2：Original S21 data are compared with filtered gradual S21 baselines, realize KID detector arrays
The baseline calibration of S21.
KID detector array S21 baseline calibration methods above-mentioned based on Kalman filtering, which is characterized in that the step
Rapid one includes：
Step 1a：The measurement data of KID detector array S21 baselines is subjected to positive and reverse Kalman filtering respectively；
Step 1b：Average, acquisition KID detectors are weighted relative to the residual error of filtering to positive and backward filtering result
The baseline of array S21.
KID detector array S21 baseline calibration methods above-mentioned based on Kalman filtering, which is characterized in that the step
Suddenly 1a includes：
An initial residual error parameter is arranged in Kalman filter, the smoothness for regulating and controlling Kalman filtering output, or
Person is low-pass filtering bandpass characteristics, by it is forward and inverse to Kalman adaptive-filterings obtain base-line data.
KID detector array S21 baseline calibration methods above-mentioned based on Kalman filtering, which is characterized in that the step
Suddenly 1a includes：
Step 1a1：Positive Kalman filtering is carried out to KID detector array S21 measurement data, obtains forward filtering result
With positive variance；
Step 1a2：Reverse Kalman filtering is carried out to KID detector array S21 measurement data, obtain backward filtering result and
Reverse variance.
KID detector array S21 baseline calibration methods above-mentioned based on Kalman filtering, which is characterized in that the step
Suddenly 1b includes：
Step 1b1：By positive and reverse Kalman filtered results, positive and reverse variance is weighted averagely,
To obtain KID detector array S21 baselines；
Step 1b2：Original S21 data are compared with the S21 baselines obtained by Kalman filtering, are finally completed
KID detector array S21 baseline calibrations.
KID detector array S21 baseline calibration methods above-mentioned based on Kalman filtering, which is characterized in that the step
Suddenly 1b includes：The average weighted formula of positive and reverse Kalman filtered results：
Wherein, Xf, Xb are positive and reverse Kalman filtered results respectively, and Vxf, Vxb are positive and inverse respectively
To Kalman filtering residual error.
KID detector array S21 baseline calibration methods above-mentioned based on Kalman filtering, which is characterized in that the step
The parameter of initial residual error is 0.01~0.5 in rapid 1b.
The invention has the beneficial effects that：The KID detector array S21 baseline calibrations based on Kalman filtering of the present invention
Method has many advantages, such as simple, flexible, and can disposably complete KID detector array baseline calibrations, it is preferable to obtain consistency
Effect is calibrated, the S21 baseline calibrations of extensive KID detector arrays different situations are suitable for.
Description of the drawings
Fig. 1 is the flow chart of the KID detector array S21 baseline calibration methods the present invention is based on Kalman filtering；
Fig. 2 is the further specific reality of the KID detector array S21 baseline calibration methods the present invention is based on Kalman filtering
Apply flow chart.
Specific implementation mode
Specific introduce is made to the present invention below in conjunction with the drawings and specific embodiments.
Shown in referring to Fig.1, the present invention proposes a kind of novel KID detector array S21 baseline calibration methods.This method
Adaptive-filtering is carried out to KID detector array S21 data using Kalman filtering, obtains the gradual S21 with low frequency characteristic
Baseline, and original KID detector array S21 data are led into baseline with the S21 after Kalman filtering and are subtracted each other, it is disposable to realize
The S21 baseline calibrations of KID detector arrays, since Kalman filtering has the characteristics that adaptive, and calibration process is disposably automatic
It completes, therefore this method is suitable for the S21 baseline calibrations of extensive KID detector arrays different situations.
Based on Kalman filtering KID detector array S21 baseline calibration methods, concrete scheme is：By KID detector arrays
S21 measurement data carries out positive and reverse Kalman filtering respectively, and to positive and backward filtering result relative to the residual of filtering
Poor (covariance) is weighted average, the baseline of acquisition KID detector arrays S21, and by original S21 data in filtered
Baseline is compared and (subtracts each other), realizes the baseline calibration of KID detector arrays S21.In this scenario, Kalman filter is arranged
One initial residual error parameter, smoothness or low-pass filtering bandpass characteristics for regulating and controlling Kalman filtering output, passes through
Just, reverse Kalman adaptive-filterings obtain base-line data.As it can be seen that this method has ID detector array S21 baseline calibrations
Have it is flexible, conveniently, the features such as calibration accuracy is high.
Fig. 2 gives the schematic diagram of the acquisition of the KID detector array S21 baselines based on kalman filter method.Formula 1 is given
Positive and reverse Kalman filtered results weighted averages are gone out.
Wherein, Xf、XbIt is positive and reverse Kalman filtered results, V respectivelyxf、VxbPositive and reverse Kalman filter respectively
Wave residual error；S in Fig. 221(f) it is KID detector array S21 measurement data, S '21(f) it is KID detector array S21 baselines.
In view of the detector of KID resonator Q value in 104~106 magnitudes, the S21 bases of gradual fluctuating
An initial residual error parameter may be selected without obvious overlapping in the low-frequency component of line and the radio-frequency component of resonance frequency absorption peak profile
Be 0.01~0.5, so as to preferably regulate and control the smooth effect of Kalman filtering and avoid KID detector resonator absorption peak
The excess smoothness of profile.Further specific implementation process is as follows：
Step 1：Positive Kalman filtering is carried out to KID detector array S21 measurement data, obtains forward filtering result
With positive variance；
Step 2：Reverse Kalman filtering is carried out to KID detector array S21 measurement data, obtain backward filtering result and
Reverse variance；
Step 3：By positive and reverse Kalman filtered results, positive and reverse variance is weighted it is average, from
And obtain KID detector array S21 baselines；
Step 4：Original S21 data are compared with the S21 baselines obtained by Kalman filtering, are finally completed
KID detector array S21 baseline calibrations.
As it can be seen that it is proposed by the present invention based on Kalman filtering KID detector array S21 baseline calibration methods have it is simple,
The advantages that flexible, and KID detector array baseline calibrations can be disposably completed, it obtains consistency and preferably calibrates effect, be applicable in
In the S21 baseline calibrations of extensive KID detector arrays different situations.
The basic principles, main features and advantages of the invention have been shown and described above.The technical staff of the industry should
Understand, the invention is not limited in any way above-described embodiment, all to be obtained by the way of equivalent substitution or equivalent transformation
Technical solution is all fallen in protection scope of the present invention.
Claims (4)
1. the KID detector array S21 baseline calibration methods based on Kalman filtering, which is characterized in that include the following steps：
Step 1：Adaptive-filtering is carried out to KID detector array S21 data using Kalman filtering, obtaining has low frequency special
The gradual S21 baselines of property；
Step 2：Original S21 data are compared with filtered gradual S21 baselines, realize KID detector arrays S21
Baseline calibration；
The step 1 includes：
Step 1a：The measurement data of KID detector array S21 baselines is subjected to positive and reverse Kalman filtering respectively；
Step 1b：Average, acquisition KID detector arrays are weighted relative to the residual error of filtering to positive and backward filtering result
The baseline of S21；
The step 1a includes：
An initial residual error parameter is arranged in Kalman filter, the smoothness for regulating and controlling Kalman filtering output, either
Low-pass filtering bandpass characteristics, by it is forward and inverse to Kalman adaptive-filterings obtain base-line data；
Step 1a1：Positive Kalman filtering is carried out to KID detector array S21 measurement data, obtains forward filtering result and just
To variance；
Step 1a2：Reverse Kalman filtering is carried out to KID detector array S21 measurement data, obtains backward filtering result and reverse
Variance.
2. the KID detector array S21 baseline calibration methods according to claim 1 based on Kalman filtering, feature
It is, the step 1b includes：
Step 1b1：By forward direction and reverse Kalman filtered results, positive and reverse variance is weighted averagely, thus
Obtain KID detector array S21 baselines；
Step 1b2：Original S21 data are compared with the S21 baselines obtained by Kalman filtering, are finally completed KID
Detector array S21 baseline calibrations.
3. the KID detector array S21 baseline calibration methods according to claim 2 based on Kalman filtering, feature
It is, the step 1b includes：The average weighted formula of positive and reverse Kalman filtered results：
Wherein, Xf、XbIt is positive and reverse Kalman filtered results, V respectivelyxf、VxbPositive and reverse Kalman filtering is residual respectively
Difference.
4. the KID detector array S21 baseline calibration methods according to claim 3 based on Kalman filtering, feature
It is, the parameter of initial residual error is 0.01~0.5 in the step 1b.
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