CN108254730B - Radar zero-time-delay autocorrelation function processing method based on damping fitting - Google Patents
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Abstract
The invention discloses a radar zero-delay-position autocorrelation function processing method based on damping fitting, which mainly solves the problem that the information of a zero delay position cannot be accurately acquired when an ionosphere is detected by the conventional incoherent scattering radar. The implementation scheme is as follows: 1) calculating a combined measured autocorrelation value L by using an algorithm; 2) establishing a damping function model, and setting the value range and the search step length of each parameter in the model; 3) obtaining a combined fitting autocorrelation value S expression according to the damping function model, selecting parameters for multiple times in a parameter value range, calculating the corresponding sum of squares of residual errors by L and S, and comparing to obtain the minimum sum of squares of residual errors; 4) and determining a final damping function model according to the least residual error square and the corresponding parameter value, thereby calculating to obtain a zero-time-delay fitting autocorrelation value. The processing process of the invention is simple and easy to realize, and the data information at the zero time delay position is reserved, thus making up the defects of the existing incoherent scattering radar in the aspect of zero time delay autocorrelation function processing.
Description
Technical Field
The invention belongs to the technical field of information processing, and particularly relates to an autocorrelation function estimation algorithm and a damping fitting method of an incoherent scattering radar, in particular to a radar zero-time-delay autocorrelation function processing method based on damping fitting, which can be used for calculating an autocorrelation value of the incoherent scattering radar at a zero-time delay.
Background
The ionosphere, as an important component in the near-earth space environment, directly has a great influence on activities such as weather monitoring, broadcasting, radar positioning, radio navigation and the like, so that the ionosphere detection is of great importance. Common ionosphere detection means include vertical detection, oblique detection, coherent scatter radar detection, incoherent scatter radar detection, and the like. The incoherent scattering radar has the outstanding advantages of multiple measurement parameters, wide coverage space range, high space-time resolution and the like, and becomes the strongest means for ground observation of the ionosphere at present. However, due to the difficulty in construction and high operation cost, only about ten incoherent scattering radars exist in the world at present. The first set of incoherent scattering radars in China was initially built in Yunnan Qujing in 2012, and have important significance for ionospheric space weather monitoring and research in low latitude areas in China.
The signal processing method of the incoherent scattering radar is different from that of the traditional radar aiming at ionospheric targets distributed continuously in a large range. The ionosphere echo signal is mainly an incoherent scattering signal caused by scattering of electrons, ions and the like, is a typical random signal, has stationarity in a short time of several minutes, and can be used for representing the statistical characteristics of the signal by calculating an autocorrelation function and power spectral density; the ionosphere is a typical soft target, radar echo signals at different heights are mutually aliased, and distance ambiguity needs to be eliminated through an effective signal coding design and a special signal processing algorithm. The purpose of incoherent scattering radar signal processing is to obtain autocorrelation values or power spectrums at different time delays and prepare for subsequent inversion work.
In the incoherent scattering signal processing, the autocorrelation function at the zero time delay is required to be additionally processed because the autocorrelation function at the zero time delay is poor in balance at different time delays and influences the estimation performance of the ionospheric scattering spectrum due to large height ambiguity and low resolution at the zero time delay. An article "The use of multi-pulse zero lag data to impulse coherent rake power acquisition" published in 1986 by Markku s.lehtinen and Asko Huuskonen of The university of orlu, finland, in Journal of aggregate and terrestial Physics "discloses a method for acquiring zero-delay information, which discards zero-delay data generated during incoherent scattered signal processing and retransmits a single pulse or a barker code of different frequencies to acquire data information at zero-delay. Obviously, the method requires that the incoherent scattering radar has a single pulse or Barker code coding mode. However, the first set of incoherent scattering radar built by yunnan qujing in China only has two coding modes of long pulse coding and two-phase alternate coding, and has great difficulty in acquiring information at zero time delay, and the method proposed by the university of Oluo is not suitable for incoherent scattering radar in China.
Disclosure of Invention
The invention aims to provide a radar zero-delay autocorrelation function processing method based on damping fitting aiming at the defects of the incoherent scattering radar zero-delay autocorrelation function processing method in the prior art, so as to solve the problem that the information at the zero-delay position cannot be accurately acquired when the incoherent scattering radar detects an ionosphere.
The specific idea for realizing the purpose of the invention is as follows: 1) calculating the actually measured autocorrelation function values of the time delays from one to eight to obtain the combined actually measured autocorrelation values; 2) establishing a damping function model, and setting the value range and the search step length of each parameter in the model; 3) obtaining a fitting autocorrelation function expression of time delay one to eight according to the damping function model, selecting parameters for multiple times in a parameter value range, calculating by combining the actually measured autocorrelation value and the fitting autocorrelation function expression to obtain different square sums of multiple residual errors, and comparing to obtain the minimum square sum of the residual errors; 4) determining a final damping function model according to the least residual error square and the corresponding parameter value; thus solving the autocorrelation function value at zero time delay. And the accurate acquisition of the information at the zero time delay position is realized.
The invention realizes the aim as follows:
(1) calculating a combined measured autocorrelation value:
(1.1) acquiring ionosphere scattering original echo data D in an incoherent scattering radar receiver;
(1.2) filtering the original echo data D by using a Gaussian filter to obtain filtered data D1;
(1.3) translating the filtered data D1 by i symbols to obtain second filtered data D2, and obtaining an actually measured autocorrelation value L (i) at the time delay i according to the following formula:
L(i)＝D1×D2，
wherein i is 0,1,2, 1, m-1, m is the number of the transmitting signal code elements and m is more than or equal to 9;
(1.4) taking the time delay i to be 1 to 8, respectively calculating the actual measurement autocorrelation values of the time delays 1 to 8 according to the step (1.3), and obtaining a combined actual measurement autocorrelation value L:
L＝[L(1),L(2),…,L(8)]；
(2) establishing a damping function model:
assuming ionospheric scattering spectrum c (v):
wherein v represents frequency, A1For the scattering spectrum amplitude, ε is the spectral line half-width, v0Is the spectrum center frequency, and Δ v is the difference between the spectrum peak frequency and the spectrum center frequency;
performing inverse Fourier transform on C (v) to obtain an ionospheric autocorrelation function I (t), namely a damping function model:
where IDFT denotes inverse Fourier transform, t denotes time, A1For the scatter spectrum amplitude, δ represents the damping coefficient, ω r2 pi/T represents the damping vibration angular frequency, and T represents the damping vibration period;
setting A in a damping function model according to the combined measured autocorrelation value1The parameter value range of (2); setting omega according to main concentrated frequency interval of ionospheric scattering spectrumrAnd the parameter value range of delta;
(3) obtaining the minimum sum of squares of residual errors:
(3.1) substituting t ═ i into formula <2>, and obtaining a fitting autocorrelation value q (i) expression at the time delay i:
q(i)＝I(i)＝2A1e-δ|i|cos(ωri) <3>
(3.2) taking the time delay i as 1 to 8, respectively obtaining fitting autocorrelation value expressions of the time delays 1 to 8 according to the step (3.1), and obtaining a combined fitting autocorrelation value S expression:
S＝[q(1),q(2),…,q(8)] <4>
(3.3) according to the parameter A set in the step (2)1、ωrAnd delta value range, respectively setting the search step length;
(3.4) setting the parameter A in advance1、ωrAnd within the value range of delta, respectively selecting the minimum value of each parameter as an initial parameter value, and according to a formula<5>Solving a first residual error square sum;
solving the sum of squared residual errors sigma2The formula of (1) is as follows:
σ2＝[S-L][S-L]T <5>
wherein, the [ alpha ], [ beta ] -a]TRepresenting a transpose operation;
to A1、ωrAnd the initial parameter values of delta are respectively increased progressively according to the set search step length;
(3.5) judging the size of the parameter after increasing:
if the parameter A is increased1、ωrIf the sum delta is smaller than the maximum value of the parameter value range, entering the step (3.6);
if the parameter A is increased1、ωrIf any one of the sum delta is larger than or equal to the maximum value of the parameter value range, entering the step (3.7);
(3.6) obtaining the sum of squares of residual errors corresponding to the parameters after the incremental parameters according to a formula <5>, increasing the incremental parameters again according to the search step length of the incremental parameters, and then returning to the step (3.5) to judge the parameters after the incremental parameters are increased again;
(3.7) comparing the obtained sum of squares of all residual errors to obtain the minimum sum of squares sigma of residual errorsmin 2；
(4) Calculating a zero-time delay fitting autocorrelation value:
let the minimum sum of squared residual errors σmin 2The corresponding parameter value is the final scattering spectrum amplitude A'1Ultimate damped angular vibration frequency ω'rAnd the final damping coefficient delta', substituted into the formula<2>Obtaining a final damping function expression:
I'(t)＝2A'1e-δ'|t|cos(ω'rt)，
and calculating to obtain a zero time delay fitting autocorrelation value q (0) by the following formula:
q(0)＝I'(0)＝2A'1。
compared with the prior art, the invention has the following advantages:
firstly, because the incoherent scattering radar does not need to be subjected to additional monopulse coding or bark coding, the design cost of the radar is reduced, the use times of the radar are reduced, and the operation and maintenance cost is reduced;
secondly, as the processing process adopted by the invention does not involve discarding data, the data information at the zero time delay position is reserved, so that the signal processing process of the incoherent scattering radar is more perfect, and the ionosphere information is more comprehensively obtained;
thirdly, because the damping fitting is introduced into the signal processing process of the incoherent scattering radar, the time delay autocorrelation function is fitted in a damping fitting mode, the problem of calculating the autocorrelation value at the zero time delay position is solved, and compared with the existing autocorrelation function processing method, the processing process is simpler and is easy to realize.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a fitted autocorrelation simulation plot and a measured autocorrelation simulation plot;
FIG. 3 is a graph of an autocorrelation simulation of the processing of an echo signal using a non-coherent scatter signal processing method;
FIG. 4 is a graph of an autocorrelation simulation of the processing of an echo signal using the present invention;
FIG. 5 is a simulation plot of a multi-height power spectrum for processing an echo signal using an incoherent scatter signal processing method;
FIG. 6 is a simulation plot of a multi-height power spectrum for processing echo signals using the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described with reference to the accompanying drawings and specific embodiments.
Referring to fig. 1, the specific implementation steps of the present invention are as follows:
step 1: calculating a combined measured autocorrelation value:
storing ionosphere scattering echo original data collected from an incoherent scattering radar receiver in a file form, then selecting data in the file, and carrying out incoherent scattering radar signal processing on the data, aiming at calculating a combined actual measurement autocorrelation value from time delay 1 to time delay 8 for determining damping model parameters in the following steps, wherein the specific calculation process is as follows:
(1.1) acquiring ionosphere scattering original echo data D in an incoherent scattering radar receiver;
(1.2) filtering the original echo data D by using a Gaussian filter to obtain filtered data D1; wherein the width of the impulse response of the gaussian filter is equal to the transmit signal symbol width;
(1.3) translating the filtered data D1 by i symbols to obtain second filtered data D2, and obtaining an actually measured autocorrelation value L (i) at the time delay i according to the following formula:
L(i)＝D1×D2，
wherein i is 0,1,2, 1, m-1, m is the number of the transmitting signal code elements and m is more than or equal to 9;
(1.4) taking the time delay i to be 1 to 8, respectively calculating the actual measurement autocorrelation values of the time delays 1 to 8 according to the step (1.3), and obtaining a combined actual measurement autocorrelation value L:
L＝[L(1),L(2),…,L(8)]；
the implementation steps of the method for processing the incoherent scattering radar signal in the step can be divided into: reading data, selecting a box-shaped filter, filtering the signal to eliminate noise interference and simultaneously determining an autocorrelation time delay interval; performing correlation operation on the filtered data, and calculating a time delay profile matrix; and calculating autocorrelation functions of the scattering signals in different height ranges by using the time delay profile matrix according to the coding mode, and accumulating the autocorrelation functions in different periods. Basic parameters of the incoherent scattering radar are set as follows: the transmitting frequency is 500MHz, the collecting frequency is 6.25MHz, 16-bit two-phase alternate coding is carried out, the pulse width is 480us, the time delay interval is 30us, the time delay number is 16, and the fitting adopts the time delay from 1 to 8, and the total number of the time delay points is 8.
Step 2: establishing a damping function model:
assuming ionospheric scattering spectrum c (v):
wherein v represents frequency, A1For the scattering spectrum amplitude, ε is the spectral line half-width, v0Is the spectrum center frequency, and Δ v is the difference between the spectrum peak frequency and the spectrum center frequency;
performing inverse Fourier transform on C (v) to obtain an ionospheric autocorrelation function I (t), namely a damping function model:
where IDFT denotes inverse Fourier transform, t denotes time, A1For the scatter spectrum amplitude, δ represents the damping coefficient, ω r2 pi/T denotes dampingThe vibration angular frequency, T, represents the damped vibration period;
setting A in a damping function model according to the combined measured autocorrelation value1The parameter value range of (2): a. the1The autocorrelation value L ═ L (1), L (2), …, L (8) measured by the combination]To determine, only L (1) is considered here, setting A1Has a value range of [0.3,2 ]]L(1)；
Setting omega according to main concentrated frequency interval of ionospheric scattering spectrumrAnd the parameter value range of delta: parameter omegarHas a value range of [0,1.6 ]](ii) a The value range of the parameter delta is [0,0.79 ]]；
The accurate values of all parameters in the model are unknown, and are determined in the subsequent damping fitting process through the set parameter range.
And step 3: obtaining the minimum sum of squares of residual errors:
(3.1) substituting t ═ i into formula <2>, and obtaining a fitting autocorrelation value q (i) expression at the time delay i:
q(i)＝I(i)＝2A1e-δ|i|cos(ωri) <3>
(3.2) taking the time delay i as 1 to 8, respectively obtaining fitting autocorrelation value expressions of the time delays 1 to 8 according to the step (3.1), and obtaining a combined fitting autocorrelation value S expression:
S＝[q(1),q(2),…,q(8)] <4>
(3.3) according to the parameter A set in the step (2)1、ωrAnd delta value ranges, respectively set to A1Is 0.05L (1), ωrThe search step length is 0.03, and the delta search step length is 0.03;
(3.4) setting the parameter A in advance1、ωrAnd within the value range of delta, respectively selecting the minimum value of each parameter as an initial parameter, namely: get A1Is 0.3L (1) ═ 2.0809 × 109、ωrIf 0 and δ is 0, the combined fitting autocorrelation value S and the combined measured autocorrelation value L corresponding to the parameter are respectively:
solving the sum of squared residual errors sigma2The formula of (1) is as follows:
σ2＝[S-L][S-L]T <5>
wherein, the [ alpha ], [ beta ] -a]TRepresenting a transpose operation;
according to the formula<5>The sum of the squares of the first residual error was found to be 1.5 x 1020；
To A1、ωrAnd delta, respectively increasing the initial parameter values according to the set search step length to obtain the increasing scattering spectrum amplitude A1b＝2.4277*109Increasing damping vibration angular frequency omegarb0.03, increasing the damping coefficient deltab＝0.03；
(3.5) judging the size of the parameter after increasing:
parameter A after increasing1b＜1.3873*1010，ωrb＜1.6，δbIf the value is less than 0.79, namely each parameter is less than the maximum value of the parameter value range, the step (3.6) is carried out;
(3.6) the combined fitting autocorrelation value S and the combined measured autocorrelation value L corresponding to the parameters after the incremental increase are respectively as follows:
according to the formula<5>The sum of the squared residual errors for the incremented parameters was found to be 1.4563 x 1020；
The parameters after increasing are increased again according to the searching step length to obtain the increasing scattering spectrum amplitude A1b＝2.7745*109Increasing damping vibration angular frequency omegarb0.06, increasingDamping coefficient deltabIf the value of the parameter is 0.06, returning to the step (3.5) to judge the parameter after the increment is carried out again, wherein each parameter is still smaller than the maximum value of the parameter value range, and therefore, the residual error square sum corresponding to the current parameter is continuously solved; the process is circulated until the parameters A are taken for a plurality of times and are increased in number1、ωrIf any one of the sum delta is larger than or equal to the maximum value of the parameter value range, entering the step (3.7);
27 residual error square sums obtained by multiple solving are obtained;
(3.7) comparing the obtained 27 residual error sum of squares to obtain the minimum residual error sum of squares sigmamin 2Comprises the following steps:
σmin 2＝3.8605*1018；
and 4, step 4: calculating a zero-time delay fitting autocorrelation value:
sum of squares of minimum residual error σmin 2The corresponding parameter values are: final scatter spectrum amplitude A1b＝9.0171*109Ultimate damped angular vibration frequency ω'r0.60 and the final damping coefficient δ' 0.60, which are substituted into the formula<2>Obtaining a final damping function expression:
I'(t)＝1.8034*1010*e-0.6|t|cos(0.6t)，
and calculating to obtain a zero time delay fitting autocorrelation value q (0) by the following formula:
q(0)＝I'(0)＝1.8034*1010。
the application effect of the present invention is further explained by combining the following simulation:
firstly, simulation conditions: in the Windows 7 environment, the software MATLAB is used for carrying out simulation experiments.
Secondly, simulating contents and results:
simulation 1, aiming at echo data with the height of 402km in an ionized layer, calculating an autocorrelation value (actually measured autocorrelation value) with a time delay of one to eight by using a non-coherent scattering radar signal processing method, and simulating the autocorrelation value by using MATLAB software, wherein a simulation result is shown as a marked curve of a circle in fig. 2. MATLAB simulation is carried out on the autocorrelation values of the time delay from zero to eight fitted by the damping function, and the simulation result is shown as an asterisk marked curve in figure 2.
As can be seen from fig. 2, the damping function curve is approximately the same as the autocorrelation function curve calculated by the incoherent scattering signal processing method. When the image is observed, the two images do not completely overlap due to the existence of the distance blur, but the error is within the allowable range. The simulation results show that the idea of fitting the autocorrelation function using damping is completely correct. In addition, the value of the ordinate when the abscissa is zero is the autocorrelation value at zero time delay, and the calculation is extremely simple.
And 2, aiming at echo data with the height of 402km in an ionized layer, calculating autocorrelation values at all time delays by using an incoherent scattering radar signal processing method, and simulating the autocorrelation values by using MATLAB software, wherein the simulation result is shown in figure 3.
As can be seen from fig. 3, the autocorrelation function is less well balanced at different delays because the distance at zero delay is blurred and the distance resolution is lower. The ionospheric sounding is severely affected by the imbalance of the autocorrelation function, so that additional processing of the autocorrelation function at zero time delay is necessary.
And 3, aiming at echo data with the height of 402km in an ionized layer, correcting the zero-time-delay autocorrelation value obtained by the incoherent scattering radar signal processing method by using the method described by the invention, and simulating the autocorrelation values at all time delays by using MATLAB software, wherein the simulation result is shown in FIG. 4.
As can be seen from fig. 4, compared with fig. 3, the equalization of the autocorrelation function corrected by the damping function is improved at different time delays, which is beneficial to ionospheric detection.
And 4, aiming at echo data of all heights in the ionosphere, calculating a power spectrogram of the full height by using an incoherent scattering radar signal processing method, and simulating the power spectrogram by using MATLAB software, wherein the simulation result is shown in FIG. 5.
As can be seen from fig. 5, in combination with fig. 3, since the autocorrelation value at the zero delay is much greater than the autocorrelation values at other delays, the energy of the incoherent scattering spectrum is dispersed, the side lobe is extremely high, and the estimation of each physical parameter of the ionosphere is seriously affected.
And 6, aiming at echo data of all heights in the ionosphere, correcting the zero-time-delay autocorrelation value obtained by the incoherent scattering radar signal processing method at each height by using the method described by the invention, performing Fourier transform on the zero-time-delay autocorrelation value, and simulating the transform result by using MATLAB software, wherein the simulation result is shown in FIG. 6.
As can be seen from fig. 6, compared with fig. 5, the power spectrum corrected by the damping function has more concentrated energy, which is beneficial to the estimation of each physical parameter of the ionosphere.
By combining all the simulation results, the method can effectively and conveniently calculate the autocorrelation value of the incoherent scattering radar at the zero time delay position, fully improve the balance of the autocorrelation function, improve the estimation performance of the incoherent scattering spectrum, be favorable for the detection of the ionized layer and fully embody the feasibility of the method.
The invention has not been described in detail in part of the common general knowledge of those skilled in the art.
While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (4)
1. A radar zero-time-delay autocorrelation function processing method based on damping fitting is characterized by comprising the following steps:
(1) calculating a combined measured autocorrelation value:
(1.1) acquiring ionosphere scattering original echo data D in an incoherent scattering radar receiver;
(1.2) filtering the original echo data D by using a Gaussian filter to obtain filtered data D1;
(1.3) translating the filtered data D1 by i symbols to obtain second filtered data D2, and obtaining an actually measured autocorrelation value L (i) at the time delay i according to the following formula:
L(i)＝D1×D2，
wherein i is 0,1,2, 1, m-1, m is the number of the transmitting signal code elements and m is more than or equal to 9;
(1.4) taking the time delay i to be 1 to 8, respectively calculating the actual measurement autocorrelation values of the time delays 1 to 8 according to the step (1.3), and obtaining a combined actual measurement autocorrelation value L:
L＝[L(1),L(2),…,L(8)]；
(2) establishing a damping function model:
assuming ionospheric scattering spectrum c (v):
wherein v represents frequency, A1For the scattering spectrum amplitude, ε is the spectral line half-width, v0Is the spectrum center frequency, and Δ v is the difference between the spectrum peak frequency and the spectrum center frequency;
performing inverse Fourier transform on C (v) to obtain an ionospheric autocorrelation function I (t), namely a damping function model:
where IDFT denotes inverse Fourier transform, t denotes time, A1For the scatter spectrum amplitude, δ represents the damping coefficient, ωr2 pi/T represents the damping vibration angular frequency, and T represents the damping vibration period;
setting A in a damping function model according to the combined measured autocorrelation value1The parameter value range of (2); setting omega according to main concentrated frequency interval of ionospheric scattering spectrumrAnd the parameter value range of delta;
(3) obtaining the minimum sum of squares of residual errors:
(3.1) substituting t ═ i into formula <2>, and obtaining a fitting autocorrelation value q (i) expression at the time delay i:
q(i)＝I(i)＝2A1e-δ|i|cos(ωri) <3>
(3.2) taking the time delay i as 1 to 8, respectively obtaining fitting autocorrelation value expressions of the time delays 1 to 8 according to the step (3.1), and obtaining a combined fitting autocorrelation value S expression:
S＝[q(1),q(2),…,q(8)] <4>
(3.3) according to the parameter A set in the step (2)1、ωrAnd delta value range, respectively setting the search step length;
(3.4) setting the parameter A in advance1、ωrAnd within the value range of delta, respectively selecting the minimum value of each parameter as an initial parameter value, and according to a formula<5>Solving a first residual error square sum;
solving the sum of squared residual errors sigma2The formula of (1) is as follows:
σ2＝[S-L][S-L]T <5>
wherein, the [ alpha ], [ beta ] -a]TRepresenting a transpose operation;
to A1、ωrAnd the initial parameter values of delta are respectively increased progressively according to the set search step length;
(3.5) judging the size of the parameter after increasing:
if the parameter A is increased1、ωrIf the sum delta is smaller than the maximum value of the parameter value range, entering the step (3.6);
if the parameter A is increased1、ωrIf any one of the sum delta is larger than or equal to the maximum value of the parameter value range, entering the step (3.7);
(3.6) obtaining the sum of squares of residual errors corresponding to the parameters after the incremental parameters according to a formula <5>, increasing the incremental parameters again according to the search step length of the incremental parameters, and then returning to the step (3.5) to judge the parameters after the incremental parameters are increased again;
(3.7) comparing the obtained sum of squares of all residual errors to obtain the minimum sum of squares sigma of residual errorsmin 2；
(4) Calculating a zero-time delay fitting autocorrelation value:
let the minimum sum of squared residual errors σmin 2The corresponding parameter value is the final scattering spectrum amplitude A'1Ultimate damped angular vibration frequency ω'rAnd the final damping coefficient delta', substituted into the formula<2>Obtaining a final damping function expression:
I'(t)＝2A'1e-δ'|t|cos(ω'rt)，
and calculating to obtain a zero time delay fitting autocorrelation value q (0) by the following formula:
q(0)＝I'(0)＝2A'1。
2. the method of claim 1, wherein: the basic parameters of the incoherent scattering radar in the step (1) are set as follows:
the transmitting frequency is 500MHz, the collecting frequency is 6.25MHz, 16-bit two-phase alternate coding is carried out, the pulse width is 480us, the time delay interval is 30us, the time delay number is 16, and the fitting adopts the time delay from 1 to 8, and the total number of the time delay points is 8.
3. The method of claim 1, wherein: and (3) the width of the impulse response of the Gaussian filter in the step (1.2) is equal to the width of the code element of the transmitted signal.
4. The method of claim 1, wherein: the value range of the damping function model parameter in the step (2) is set as follows:
parameter A1Has a value range of [0.3,2 ]]L (1), the search step length is 0.05L (1); parameter omegarHas a value range of [0,1.6 ]]The search step length is 0.03; the value range of the parameter delta is [0,0.79 ]]And the search step size is 0.03.
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