CN108768560A - Adaptive non-integer delay time estimation method under low signal-to-noise ratio impulse noise environment - Google Patents

Adaptive non-integer delay time estimation method under low signal-to-noise ratio impulse noise environment Download PDF

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CN108768560A
CN108768560A CN201810417008.6A CN201810417008A CN108768560A CN 108768560 A CN108768560 A CN 108768560A CN 201810417008 A CN201810417008 A CN 201810417008A CN 108768560 A CN108768560 A CN 108768560A
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time delay
sequence
value
covariation
signal
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刘文红
李均浩
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Shanghai Dianji University
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Shanghai Dianji University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/364—Delay profiles

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  • Quality & Reliability (AREA)
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Abstract

The present invention provides the adaptive non-integer delay time estimation methods under a kind of low signal-to-noise ratio impulse noise environment, which is characterized in that includes the following steps：Observation sequence is carried out from co-variation and mutual co-variation operation, covariation sequence is subjected to correlation method time delay estimation, obtains the integer-bit of time delay estimated value, the iteration initial value as LMPFTDE algorithms；Then using covariation sequence as the input signal of LMPFTDE algorithms, iteration obtains non-integer time delay estimated value under least mean p-norm criterion；Use the median of convergence process iteration time delay value as time delay estimated value.In the present invention, observation sequence has slackened uncorrelated noise influence by co-variation processing, enhances signal-to-noise ratio, pulsive noise is also inhibited, while relevant information between stick signal；After co-variation is handled, signal length doubles observation sequence, can carry out iteration more times, and more iterative values references can make time delay estimated value closer to actual value.

Description

Adaptive non-integer delay time estimation method under low signal-to-noise ratio impulse noise environment
Technical field
The present invention relates to the adaptive non-integer delay time estimation methods under a kind of low signal-to-noise ratio impulse noise environment, belong to micro- The adaptive processing technique field of weak signal.
Background technology
In the Time Delay Estimation Algorithms for modeling noise based on α Stable distritations, co-variation algorithm, fractional lower-order covariance method, co-variation Correlation method can estimate that integer-bit is estimated to time delay.Co-variation correlation method asks from covariation sequence and mutually total to input signal first Become sequence, co-variation operation can impulse noise mitigation, improve signal-to-noise ratio, while retaining the phase information between original signal, in low letter It makes an uproar than in impulse noise environment, co-variation cross-correlation estimation precision is higher than covariance method and correlation method.
There are two types of the resolution ratio that method can improve time delay estimation：A kind of method is interpolation；Another method is directly to estimate Count out non-integer time delay.Fractional time delay estimation method based on least mean p-norm is known as LMPFTDE algorithms, can be with The case where being directly the non-integer sampling interval to time delay true value, is estimated.Time delay estimation procedure is：It is with a coefficient The filter of sinc sampling functions carrys out fit time delay, to time delay and signal-to-noise ratio two because being usually filtered device power system Several amendments；With method of relaxation, is decoupled and be converted into two one-dimensional optimization problems, be divided into two-stage cascade：Level-one is for fitting The variation of signal-to-noise ratio is answered, another grade is for tracking time delay；In regular hour delayed scope, cost function is unimodal letter Number, there is unique minimum value, using steepest descent method, replaces statistics flat using gradient technique, and with the instantaneous value of error signal Time delay and signal-to-noise ratio are iterated respectively, in the hope of optimal solution.
Time delay estimation is carried out to some low frequency signals, if sample frequency only meets sampling thheorem, the error of fractional bits is to fixed Position influence is very big；The resolution ratio of time delay estimation can be improved by improving the sample rate of signal, but correlation peak is not just sharp, is not easy to look for To the position of peak value.
The cost function of LMPFTDE algorithms is Solving Multimodal Function, but time delay value, between D-0.5 and D+0.5, D is that time delay is true Value, cost function is unimodal.So other algorithms is needed accurately to be estimated time delay value integer-bit first, as LMPFTDE algorithm iteration initial values.
Invention content
The purpose of the present invention is：The time delay value integer-bit of LMPFTDE algorithms is accurately estimated using co-variation correlation method Meter.
In order to achieve the above object, the technical solution of the present invention is to provide under a kind of low signal-to-noise ratio impulse noise environment Adaptive non-integer delay time estimation method, which is characterized in that include the following steps：
Step 1 receives signal x to two1(n) and x2(n) mutual covariation sequence R is soughtc12, docking collection of letters x1(n) it asks from altogether Become sequence Rc11, then by mutual covariation sequence Rc12, from covariation sequence Rc11As equivalent time series as LMPFTDE algorithms Input signal, with correlation method time delay estimate to mutual covariation sequence Rc12, from covariation sequence Rc11First carry out time delay estimated value integer Position estimation, using obtained estimated value as the initial value of LMPFTDE algorithm time delay value iteration；
Step 2, by mutual covariation sequence Rc12As the input signal of LMPFTDE algorithms, under least mean p-norm criterion Iteration obtains non-integer time delay estimated value；
Step 3 uses the median of convergence process iteration time delay value as time delay estimated value, obtains the time delay of higher resolution Estimated value.
In the present invention, observation sequence has slackened uncorrelated noise influence by co-variation processing, enhances signal-to-noise ratio, pulse Property noise is also inhibited, while relevant information between stick signal；For observation sequence after co-variation is handled, signal length increases by one Times, iteration more times can be carried out, more iterative values references can make time delay estimated value closer to actual value.
Description of the drawings
Fig. 1 is the flow chart of improved non-integer novel adaptive time delay estimation provided by the invention；
Fig. 2 is LMPFTDE algorithmic statement curves；
Fig. 3 is innovatory algorithm convergence curve provided by the invention；
Fig. 4 is the estimated accuracy of LMPFTDE algorithms and innovatory algorithm；
Fig. 5 is the estimated accuracy of LMPFTDE algorithms and innovatory algorithm；
Fig. 6 is the estimated accuracy of LMPFTDE algorithms and innovatory algorithm.
Specific implementation mode
In order to make the present invention more obvious and understandable, hereby with preferred embodiment, and attached drawing is coordinated to be described in detail below.
In conjunction with Fig. 1, the present invention provides the adaptive non-integer time delay estimations under a kind of low signal-to-noise ratio impulse noise environment Method includes the following steps：
Step 1 receives signal x to two1(n) and x2(n) mutual covariation sequence R is soughtc12, docking collection of letters x1(n) it asks from altogether Become sequence Rc11, then by mutual covariation sequence Rc12, from covariation sequence Rc11As equivalent time series as LMPFTDE algorithms Input signal, with correlation method time delay estimate to mutual covariation sequence Rc12, from covariation sequence Rc11First carry out time delay estimated value integer Position estimation, using obtained estimated value as the initial value of LMPFTDE algorithm time delay value iteration；
Step 2, by mutual covariation sequence Rc12As the input signal of LMPFTDE algorithms, under least mean p-norm criterion Iteration obtains non-integer time delay estimated value；
Step 3 uses the median of convergence process iteration time delay value as time delay estimated value, obtains the time delay of higher resolution Estimated value.
Experiment receives signal according to signal and noise model construction two-way, and the source signal s (n) with the flat spectrum of limit is by white Gaussian Noise by bandwidth be 0.2 6 rank Butterworth lowpass filters generate, pulsive noise by obey α Stable distritations signal Simulate, signal-to-noise ratio according toSetting, whereinIndicate the variance of source signal；rvIndicate point of noise Dissipate coefficient, take signal length n=10000, postpones signal s (n-D) by61 rank FIR filters production It is raw, set time delay true valueIterative initial value isThe length of covariation sequence is 20000 points, and following result is 50 Secondary independent experiment is averaged.
Experiment 1：Under the conditions of identical α values and MSNR, α=1.5, MSNR=0dB, LMPFTDE algorithms and innovatory algorithm Iteration step length μg、μdIt is 0.09.
As a result as shown in Figure 2 and Figure 3, LMPFTDE algorithms can be converged to close to true value, and innovatory algorithm can converge to very Near value, but there is fluctuation, LMPFTDE algorithms and innovatory algorithm convergence rate are suitable.As shown in table 1, with convergence process iteration The median of time delay value is doubled as time delay estimated value, the iterations of innovatory algorithm, and the median of iterative value is closer Time delay true value.
The estimation performance of 1 LMPFTDE algorithms of table and innovatory algorithm compares
Experiment 2：Identical α values under the conditions of different MSNR, take α=1.5, MSNR to be changed to from -15dB with the interval of 5dB 15dB。
Experiment condition 1：P=1.1, time delay convergence factor 0.06, signal-to-noise ratio iteration step length 0.065.
The results are shown in Figure 4, when signal-to-noise ratio is less than 0dB, the root-mean-square error ratio LMPFTDE algorithms of innovatory algorithm estimation Greatly；When signal-to-noise ratio is more than 0dB, the root-mean-square error ratio LMPFTDE algorithms of innovatory algorithm are small.
Experiment condition 2：P=1.1, convergence factor are 0.04.
The results are shown in Figure 5, and the estimation performance of innovatory algorithm is integrally better than LMPFTDE algorithms.
Condition 1,2 times LMPFTDE algorithms and innovatory algorithm comparison：
Signal-to-noise ratio is less than 0dB, and the innovatory algorithm estimation performance of experiment condition 2 is better than the calculations of the LMPFTDE under experiment condition 1 Method.Signal-to-noise ratio is more than 0dB, and the innovatory algorithm estimation performance of experiment condition 1 is better than the LMPFTDE algorithms of experiment condition 2.
Experiment 3：Identical MSNR under the conditions of different α values, takes MSNR=0dB, α to change to 2 from 1.2 with 0.2 interval.P= 1.15, convergence factor is 0.09.
The results are shown in Figure 6, and LMPFTDE algorithms are similar with the root-mean-square error curve tendency of innovatory algorithm, and improves and calculate The mean square error of method estimation is less than the root-mean-square error of LMPFTDE algorithms.

Claims (1)

1. the adaptive non-integer delay time estimation method under a kind of low signal-to-noise ratio impulse noise environment, which is characterized in that including with Lower step：
Step 1 receives signal x to two1(n) and x2(n) mutual covariation sequence R is soughtc12, docking collection of letters x1(n) it asks from co-variation sequence Arrange Rc11, then by mutual covariation sequence Rc12, from covariation sequence Rc11As equivalent time series as the defeated of LMPFTDE algorithms Enter signal, is estimated to mutual covariation sequence R with correlation method time delayc12, from covariation sequence Rc11Time delay estimated value integer-bit is first carried out to estimate Meter, using obtained estimated value as the initial value of LMPFTDE algorithm time delay value iteration；
Step 2, by mutual covariation sequence Rc12As the input signal of LMPFTDE algorithms, the iteration under least mean p-norm criterion Obtain non-integer time delay estimated value；
Step 3 uses the median of convergence process iteration time delay value as time delay estimated value, obtains the time delay estimation of higher resolution Value.
CN201810417008.6A 2018-05-03 2018-05-03 Adaptive non-integer delay time estimation method under low signal-to-noise ratio impulse noise environment Pending CN108768560A (en)

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CN111537101A (en) * 2020-06-02 2020-08-14 上海电机学院 Ultrasonic wave flight time estimation method for power station boiler temperature measurement system
CN112019284A (en) * 2020-08-27 2020-12-01 中电科仪器仪表有限公司 Narrow-band signal time difference calculation method and system under low signal-to-noise ratio

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CN105391538A (en) * 2015-10-28 2016-03-09 上海电机学院 Time delay estimation method of robustness
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111537101A (en) * 2020-06-02 2020-08-14 上海电机学院 Ultrasonic wave flight time estimation method for power station boiler temperature measurement system
CN112019284A (en) * 2020-08-27 2020-12-01 中电科仪器仪表有限公司 Narrow-band signal time difference calculation method and system under low signal-to-noise ratio

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