CN113905198A - Adaptive channel equalization method and apparatus for coaxial video transmission system, and computer storage medium - Google Patents
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Abstract
The invention provides a self-adaptive channel equalization method and device of a coaxial video transmission system and a computer storage medium, which combines the characteristic extraction of a composite video signal, the judgment of the channel compensation effect of an equalizer and the characteristic engineering, and provides a method for carrying out rapid self-adaptive equalization by using a limited equalizer coefficient search space and approximate full parameter search The speed of displaying images is increased and the robustness of the equalizing device is improved.
Description
Technical Field
The present invention relates to channel equalization techniques in the field of coaxial video transmission, and in particular, to a method and apparatus for adaptive channel equalization in a coaxial video transmission system, and a computer storage medium.
Background
The coaxial video transmission is a video signal transmission technology taking a coaxial cable as a transmission medium, and the coaxial cable is an ultra-wideband transmission medium and can transmit direct current to microwave, so the coaxial video transmission is widely applied to the fields of cable television, seismic exploration and underground mineral development.
There are two main ways of coaxial video transmission: radio frequency coaxial transmission and baseband coaxial transmission. However, whether radio frequency coaxial transmission or baseband coaxial transmission, due to the nature of coaxial cables, the longer the cable, the greater the attenuation of the signal. In addition, the coaxial video transmission also has the characteristics of frequency distortion, namely, low frequency attenuation is less, and high frequency attenuation is great. Therefore, the long-distance coaxial transmission system needs to add an equalizing device to perform interference removal, correction, compensation and the like on the distorted signal at the receiving end, so as to improve the quality of the video signal.
At present, the common automatic equalization implementation method is an adaptive filtering method, which includes two processes of training and tracking. Specifically, the equalizer receives a segment of training signal, automatically adjusts the tap coefficient of the filter, tracks the current channel characteristics, and fine-tunes if necessary. In practical application, the method can adapt to channel systems with different attenuations, so that the method has a certain application value, but the method excessively depends on the sending end to send stable pilot signals, and the time for converging to the optimal filter tap coefficient is influenced by the order of the filter.
In order to overcome the defects in the prior art, research and development personnel propose various optimization schemes. For example, patent application No. 02116131.3 entitled "synchronous data signal processing apparatus" discloses a scheme in which an equalizer updates its tap coefficients with an error signal, which can simplify blind errors, reduce the dynamic range and imply a new blind mode index loop, and since the new blind mode error needs fewer bits to represent, the mean square error in the equalizer output is only marginally increased, resulting in hardware savings in implementing the equalizer. However, in this scheme, pilot training data is not used, and tap coefficients are updated directly according to an error signal derived from data symbols generated by the equalizer, the error signal being a 0-1 sequence, so that a loss function cannot accurately measure the direct relationship between the compensation strength and the equalizer coefficients. Also disclosed is an adaptive channel equalizer and method based on ensemble learning and neural network, as disclosed in patent application No. 201910536638.X entitled "adaptive channel equalizer and method based on ensemble learning and neural network", the equalizer including: the system comprises a plurality of multi-layer perceptron neural networks, each multi-layer perceptron neural network comprises an input layer, a hidden layer and an output layer, the number of neurons of the input layer is 2s, the data of the neurons are an in-phase part and an orthogonal part of a signal and a signal delay part obtained by receiving a signal which is modulated by QPSK and transmitted through a wireless channel and then separating, and the number of the neurons of the output layer is 2, and the in-phase part and the orthogonal part of the signal which is equalized by the corresponding multi-layer perceptron neural network are respectively output; the integrated learner is used for equalizing a plurality of multilayer perceptron neural networks to obtain an in-phase part and an orthogonal part of a signal, and the in-phase part and the orthogonal part are respectively weighted and then taken as a final wireless channel equalization result. Even though the scheme uses a deep learning method to train the equalizer, the scheme cannot be used in a video decoding system with unknown pilot sequences.
Disclosure of Invention
The invention aims to provide a self-adaptive channel equalization method and device of a coaxial video transmission system and a computer storage medium, so as to solve the problems of reducing the channel attenuation of the coaxial video transmission system and reducing the equalization time, accelerating the image display speed and improving the robustness of an equalization device in a long-distance coaxial video transmission system.
In order to solve the above technical problem, the present invention provides a method for adaptive channel equalization of a coaxial video transmission system, where the method for adaptive channel equalization includes:
s1, receiving a composite video signal, the composite video signal consisting of a sync edge signal, a chrominance composite video signal and a valid data signal;
s2, decoding the composite video signal;
s3, sampling the synchronous edge signal in the decoded composite video signal to obtain synchronous edge data;
s4, extracting the features of the synchronous edge data to obtain a feature vector;
s5, when the equalizer is in a closed state, calibrating the characteristic vector;
s6, repeating S2-S3 n times, wherein n is more than or equal to 2;
s7, checking the feature vector to judge whether the feature vector meets the selection requirement: if the selection requirement is met, the verification is successful, otherwise, the S2 is repeated;
s8, judging the compensation effect of the equalizer according to the two groups of characteristic vectors and outputting the locally optimal equalizer parameters;
and S9, judging whether the automatic equalization stops: if the decision is stopped, the optimal equalizer parameters are configured, otherwise, the next set of equalizer parameters is configured and the process returns to S2.
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, S3 includes:
counting the synchronous edge information of various systems to form a synchronous edge information base;
obtaining current system information in the closing state of the equalizer, then decoding the signal, obtaining the synchronous edge width and the initial position of the corresponding system from the synchronous edge information base, sampling the synchronous edge area data, and recording as
Wherein n represents the number of sampling points, and the superscript 0 represents that the equalizer is in a closed state;
and comparing the synchronous edge data obtained by sampling with the synchronous edge information in the synchronous edge information base to obtain the system information of the synchronous edge data.
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, S4 includes:
selecting the rising segments a-b of the synchronous edge signals and extracting a trend characteristic f from the rising segments1；
Selecting attenuation sections c-d of the synchronous edge signals and extracting trend characteristics f from the attenuation sections2；
From the synchronous edge signalExtracting curvature radius characteristic f from attenuation section c-d3；
Selecting a stationary section g-h of the synchronous edge signal, and extracting a volatility characteristic f from the stationary section g-h4；
The feature vector is denoted as f1，f2，f3，f4}。
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, the trend feature f is extracted1The method comprises the following steps:
obtaining a difference sequence [ Delta S ] of the synchronization edge signala＝Sa+1-Sa，…，ΔSb-1＝Sb-Sb-1}；
Maximum point r in differential sequence1The differential value of (d) is noted as:
ΔSr1＝max({ΔSa，ΔSa+1，…，ΔSb-1})；
to a point r1And p on the left and right1The points are fitted by using a least square method, and the first derivative is taken as a trend characteristic f1：
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, the trend feature f is extracted2The method comprises the following steps:
obtaining a sequence of signal differences, { Δ S }c＝Sc+1-Sc，…，ΔSd-1＝Sd-Sd-1}；
Maximum point r in differential sequence2The differential value of (d) is noted as:
ΔSr2＝max({ΔSc，ΔSc+1，…，ΔSd-1})；
to a point r2And p on the left and right2The points are fitted by using a least square method, and the first derivative is taken as a trend characteristic f2：
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, the curvature radius feature f is extracted3The method comprises the following steps:
calculating a second order difference sequence [ Delta ]2Sc＝ΔSc+1-ΔSc，…，Δ2Sd-2＝ΔSd-1-ΔSd-2}；
Minimum point r in second order difference3The differential value of (d) is given as:
Δ2Sr3＝min({Δ2Sc，Δ2Sc+1，…，Δ2Sd-2})；
to a point r3And p on the left and right3The points are fitted using a least squares method to obtain a first order difference sequence:
in a first order difference sequence, point r3And p on the left and right4The slope of the straight line fitted to a point is approximated as the second derivative of that point:
calculating the point r3The radius of curvature is the radius of curvature characteristic f3：
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, the volatility characteristic f is extracted4The method comprises the following steps:
under the condition of no interference, setting the average value of the signals close to the h point to be approximately equal to the average value of the whole data;
obtaining p around h point5Mean of points
Characteristic of fluctuation f4Is { Sg，Sg+1，…，ShRelative to
Sum of squared average errors of:
optionally, in the adaptive channel equalization method for a coaxial video transmission system, the equalizer includes discrete m equalizers { q }1,q2，…，qmThe m equalizers are obtained by using a proper interpolation method based on the relation between a compensation frequency curve of the analog equalizer and parameter change;
s5 includes:
when the equalizer is in a closed state, the calculated eigenvector value is taken
Wherein j is 1,2,3, 4;
let u set of reference features { F1，F2，…，FuAnd k sets of search start indices I1，I2，…，IkAnd (c) the step of (c) in which,
a feature vector representing the i-th set of calibrations, i ═ 1,2, … …, u;
calculating each group of calibration characteristics and F in sequence0Absolute difference of (2)
Let all Δ F0iMinimum value of is δ1＝min{ΔFUiAt maximum value δ2＝max{ΔF0iAnd define FiAnd F0Correlation coefficient of j-th feature
Where ρ represents a resolution coefficient;
calculating each set of calibration features and F0Degree of association of
Outputting search indexes
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, S7 includes:
let t-group characteristics of w-th group equalizer output be
For the trend feature f1Trend characteristic f2Radius of curvature characteristic f3And a volatility characteristic f4And (3) checking independently: let the variance
Wherein
The mean value is represented by the average value,
j represents the j-th characteristic value of the i-th repeated test, j is 1, …, 4;
calculating characteristicsChecking threshold T of sign jj: under the condition that the confidence coefficient is 95%, the critical value of t times of verification is recorded as v (t), and then
If σ (j) > TjThen the verification of the feature j is failed.
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, S8 includes:
establishing a trend feature f1Trend characteristic f2Radius of curvature characteristic f3And a volatility characteristic f4To obtain the changed trend characteristics
Trend characteristics
Radius of curvature feature
And wave characteristics
Wherein f is1bestIs a trend feature f1Taking the value when the equalization effect is best;
confirming changed trend characteristic trend characteristics by using principal component analysis method
Trend characteristics
Radius of curvature feature
And wave characteristics
Weight in decision hierarchy [ w ]1，w2，…，w4]；
Calculating a response value
And selecting the maximum response value as the locally optimal equalizer parameter output.
Optionally, in the adaptive channel equalization method of the coaxial video transmission system, S9 includes:
according to the c group equalizer qcResponse value of
And an optimal equalizer qbResponse value of
Whether or not to stop the automatic equalization in advance is judged.
In order to solve the above technical problem, the present invention further provides an adaptive channel equalization apparatus for a coaxial video transmission system, configured to implement the adaptive channel equalization method for a coaxial video transmission system as described in any one of the above embodiments, where the adaptive channel equalization apparatus includes a coaxial video signal processor and an equalizer;
the coaxial video signal processor comprises a decoding unit and a sampling unit; the decoding unit is used for decoding a video signal so as to synchronize each line of signals of the video signal; the sampling unit is used for acquiring all synchronous edge data in the decoded video signal when the equalizer is in a closed state;
the equalizer comprises a feature extraction unit, a parameter pre-screening unit, a feature verification unit, an optimal feature selection unit, a termination judgment unit and a parameter output unit; the feature extraction unit is used for performing feature calculation on the synchronous edge data to obtain a feature vector; the parameter pre-screening unit is pre-stored with a plurality of equalizer parameters and is used for calibrating the characteristic vector when the equalizer is in a closed state; the characteristic checking unit is used for checking the characteristic vector to judge whether the characteristic vector meets the selection requirement; the optimal feature selection unit is used for judging the compensation effect of the equalizer according to the two groups of feature vectors; the termination judging unit is used for judging whether to stop the automatic balancing strategy or not; the parameter output unit is used for outputting the parameters of the equalizer with the optimal compensation effect.
To solve the above technical problem, the present invention further provides a computer storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the adaptive channel equalization method for a coaxial video transmission system according to any one of the above.
The invention provides a self-adaptive channel equalization method and a device thereof and a computer storage medium of a coaxial video transmission system, which combine the characteristic extraction of a composite video signal, the judgment of the channel compensation effect of an equalizer and the characteristic engineering, and provide a method for carrying out rapid self-adaptive equalization by using a limited equalizer coefficient search space and approximate full parameter search The speed of displaying images is increased and the robustness of the equalizing device is improved.
Drawings
Fig. 1 is a flowchart of an adaptive channel equalization method of a coaxial video transmission system according to this embodiment;
fig. 2 is a schematic structural diagram of an adaptive channel equalization apparatus of a coaxial video transmission system according to this embodiment;
fig. 3 is a schematic diagram illustrating the composition of a composite video signal provided in this embodiment;
fig. 4 is a schematic diagram of the response of the synchronous edge signal when the compensation strength of the equalizer provided in this embodiment is from weak to strong.
Detailed Description
The adaptive channel equalization method and apparatus, and computer storage medium for a coaxial video transmission system according to the present invention are described in further detail with reference to the accompanying drawings and specific embodiments. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention. Further, the structures illustrated in the drawings are often part of actual structures. In particular, the drawings may have different emphasis points and may sometimes be scaled differently.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the accompanying drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order, and it is to be understood that such structures as are used are interchangeable where appropriate. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
This embodiment provides an adaptive channel equalization method for a coaxial video transmission system, as shown in fig. 1, where the adaptive channel equalization method includes:
s1, receiving a composite video signal, the composite video signal consisting of a sync edge signal, a chrominance composite video signal and a valid data signal;
s2, decoding the composite video signal;
s3, sampling the synchronous edge signal in the decoded composite video signal to obtain synchronous edge data;
s4, extracting the features of the synchronous edge data to obtain a feature vector;
s5, when the equalizer is in a closed state, calibrating the characteristic vector;
s6, repeating S2-S3 n times, wherein n is more than or equal to 2;
s7, checking the feature vector to judge whether the feature vector meets the selection requirement: if the selection requirement is met, the verification is successful, otherwise, the S2 is repeated;
s8, judging the compensation effect of the equalizer according to the two groups of characteristic vectors and outputting the locally optimal equalizer parameters;
and S9, judging whether the automatic equalization stops: if the decision is stopped, the optimal equalizer parameters are configured, otherwise, the next set of equalizer parameters is configured and the process returns to S2.
The adaptive channel equalization method for the coaxial video transmission system provided by this embodiment combines the feature extraction of the composite video signal, the channel compensation effect of the decision equalizer and the feature engineering, and provides a method for carrying out fast adaptive equalization by using a finite equalizer coefficient search space and approximate full parameter search, designs an adaptive channel equalization method which does not depend on pilot signals and uses the attenuation characteristic of a composite video signal to quickly select equalizer coefficients, so as to reduce the channel attenuation of the coaxial video transmission system, shorten the equalization time of the long-distance coaxial cable video transmission system and accelerate the speed of displaying images, meanwhile, the robustness of the equalizing device is improved, the problem of reducing the channel attenuation of the coaxial video transmission system is solved, and how to reduce the equalization time, accelerate the speed of displaying images and improve the robustness of the equalization device in the long-distance coaxial video transmission system.
Specifically, in this embodiment, step S3 includes:
s31, counting the synchronous edge information of various systems to form a synchronous edge information base;
s32, under the state of equalizer closing, obtaining current system information, then decoding the signal, obtaining the synchronous edge width and initial position of corresponding system from the synchronous edge information base, sampling the synchronous edge area data, and marking as
Wherein n representsThe number of sampling points, and the superscript 0 represents that the equalizer is in a closed state;
and S33, comparing the sampled synchronous edge data with the synchronous edge information in the synchronous edge information base to obtain the format information of the synchronous edge data.
It should be noted that, in this embodiment, the equalizer is turned off only when n operations of S6 are performed for the first time, and signal sampling is performed in a state where the equalizer is configured for subsequent operations. In addition, in this embodiment, the way to acquire the current system information is to use an automatic system detection module in the existing video decoding to acquire the current system information.
Step S4 includes:
s41, selecting the rising segment a-b of the synchronous edge signal and extracting a trend feature f from the rising segment a-b1(ii) a Specifically, the trend feature f can be extracted1The method comprises the following steps:
obtaining a difference sequence [ Delta S ] of the synchronization edge signala＝Sa+1-Sa，…，ΔSb-1＝Sb-Sb-1}；
Maximum point r in differential sequence1The differential value of (d) is noted as:
ΔSr1＝max({ΔSa，ΔSat1，…，ΔSb-1})；
to a point r1And p on the left and right1The points are fitted by using a least square method, and the first derivative is taken as a trend characteristic f1：
S42, selecting the attenuation sections c-d of the synchronous edge signals and extracting a trend feature f from the attenuation sections2(ii) a Specifically, the trend feature f is extracted2The method comprises the following steps:
obtaining a sequence of signal differences, { Δ S }c＝Sct1-Sc，…，ΔSd-1＝Sd-Sd-1}；
Maximum point r in differential sequence2Difference of (2)The score was noted as:
ΔSr2＝max({ΔSc，ΔSc+1，…，ΔSd-1})；
to a point r2And p on the left and right2The points are fitted by using a least square method, and the first derivative is taken as a trend characteristic f2：
S43, extracting curvature radius characteristic f from attenuation sections c-d of the synchronous edge signal3(ii) a Specifically, the curvature radius feature f is extracted3The method comprises the following steps:
calculating a second order difference sequence [ Delta ]2Sc＝ΔSct1-ΔSc，…，Δ2Sd-2＝ΔSd-1-ΔSd-2}；
Minimum point r in second order difference3The differential value of (d) is given as:
Δ2Sr3＝min({Δ2Sc，Δ2Sc+1，…，Δ2Sd-2})；
to a point r3And p on the left and right3The points are fitted using a least squares method to obtain a first order difference sequence:
in a first order difference sequence, point r3And p on the left and right4The slope of the straight line fitted to a point is approximated as the second derivative of that point:
calculating the point r3The radius of curvature is the radius of curvature characteristic f3：
S44, selecting the stationary segment g-h of the synchronous edge signal and extracting the volatility characteristic f from the stationary segment g-h4(ii) a Specifically, the volatility characteristic f is extracted4The method comprises the following steps:
under the condition of no interference, setting the average value of the signals close to the h point to be approximately equal to the average value of the whole data;
obtaining p around h point5Mean of points
Characteristic of fluctuation f4Is { Sg，Sgt1，…，ShRelative to
Sum of squared average errors of:
s45, representing the feature vector as f1，f2，f3，f4}。
In this embodiment, based on the variation relationship between the carrier signal trend and the signal compensation intensity, four feature calculation methods are provided to convert the one-dimensional data signal of the synchronous edge signal segment on the carrier into a discrete feature vector; constructing a characteristic discrimination model for quantitatively analyzing the channel compensation effect; and an approximate full-parameter search of an equalizer discrete search space is constructed, so that the time consumption of an automatic strategy can be effectively reduced.
In this embodiment, the equalizer comprises discrete m equalizers { q }1,q2，…，qmAnd the m equalizers are obtained by using a proper interpolation method based on the relation between the compensation frequency curve of the analog equalizer and the parameter change.
Step S5 includes:
s51, inWhen the equalizer is in a closed state, the calculated characteristic vector value
Wherein j is 1,2,3, 4;
s52, set u reference features { F }1，F2，…，FuAnd k sets of search start indices I1，I2，…，IkAnd (c) the step of (c) in which,
a feature vector representing the i-th set of calibrations, i ═ 1,2, … …, u;
s53, sequentially calculating each group of calibration characteristics and F0Absolute difference of (2)
S54, setting all DeltaF0iMinimum value of is δ1＝min{ΔFUiAt maximum value δ2＝max{ΔF0iAnd define FiAnd F0Correlation coefficient of j-th feature
Where ρ represents a resolution coefficient;
s55, calculating each group of calibration characteristics and F0Degree of association of
Outputting search indexes
Step S7 includes:
s71, setting t group characteristics of w group equalizer output as
S72, aiming at the trend characteristic f1Trend characteristic f2Radius of curvature characteristic f3And a volatility characteristic f4And (3) checking independently: let the variance
Wherein
The mean value is represented by the average value,
j represents the j-th characteristic value of the i-th repeated test, j is 1, …, 4;
s73, calculating the check threshold T of the characteristic jj: under the condition that the confidence coefficient is 95%, the critical value of t times of verification is recorded as v (t), and then
S74, if σ (j) > TjThen the verification of the feature j is failed.
Step S8 includes:
s81, establishing a trend characteristic f1Trend characteristic f2Radius of curvature characteristic f3And a volatility characteristic f4To obtain the changed trend characteristics
Trend characteristics
Radius of curvature feature
And wave characteristics
Wherein f is1bestIs a trend feature f1Taking the value when the equalization effect is best;
s82, confirming the trend characteristic after change by using principal component analysis method
Trend characteristics
Radius of curvature feature
And wave characteristics
Weight in decision hierarchy [ W1，W2，…，w4]；
S83, calculating the response value
And selecting the maximum response value as the locally optimal equalizer parameter output.
Step S9 includes:
according to the c group equalizer qcResponse value of
And an optimal equalizer qbResponse value of
Whether or not to stop the automatic equalization in advance is judged.
The present embodiment further provides an adaptive channel equalization apparatus for a coaxial video transmission system, as shown in fig. 2, the adaptive channel equalization apparatus includes a coaxial video signal processor and an equalizer.
Specifically, the coaxial video signal processor comprises a decoding unit and a sampling unit; the decoding unit is used for decoding a video signal so as to synchronize each line of signals of the video signal; the sampling unit is used for acquiring all synchronous edge data in the decoded video signal when the equalizer is in a closed state;
the equalizer comprises a feature extraction unit, a parameter pre-screening unit, a feature verification unit, an optimal feature selection unit, a termination judgment unit and a parameter output unit; the feature extraction unit is used for performing feature calculation on the synchronous edge data to obtain a feature vector; the parameter pre-screening unit is pre-stored with a plurality of equalizer parameters and is used for calibrating the characteristic vector when the equalizer is in a closed state; the characteristic checking unit is used for checking the characteristic vector to judge whether the characteristic vector meets the selection requirement; the optimal feature selection unit is used for judging the compensation effect of the equalizer according to the two groups of feature vectors; the termination judging unit is used for judging whether to stop the automatic balancing strategy or not; the parameter output unit is used for outputting the parameters of the equalizer with the optimal compensation effect.
The present embodiment also provides a computer storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the adaptive channel equalization method of the coaxial video transmission system according to the present embodiment.
Hereinafter, the application of the adaptive channel equalization method and apparatus for a coaxial video transmission system according to the present invention will be described with reference to fig. 1 to 4.
Each line of the composite video signal sent by the sending end is composed of a synchronization edge region S, a chrominance carrier region C and an effective data region V, as shown in fig. 3.
The process of obtaining the optimal configuration of the equalizer is roughly as follows:
the decoding unit decodes video signals of a system communicated with the coaxial cable; the sampling unit samples the synchronous edge signal in the closing state of the equalizer; the feature extraction unit is used for extracting features of the sampled data to obtain feature vectors; the parameter pre-screening unit pre-screens the searching parameters of the equalizer to reduce the self-adaptive equalization convergence time; after each group of configuration takes effect, repeatedly executing the sampling and feature extraction processes for a plurality of times; inputting the feature vector into a feature verification unit to perform feature data robustness verification, if the difference is small, the verification is successful, otherwise, the feature verification fails, and restarting the system from a decoding unit; the optimal characteristic selection unit judges whether the compensation effect of the current equalizer is better or not, outputs a local optimal equalizer and characteristics, compares the local optimal equalizer and the characteristics with the characteristics of the next group of equalizers in subsequent execution and updates the parameters of the discriminant model at the same time; the termination judging unit judges whether the automatic equalization is stopped or not, if the automatic equalization is stopped, the parameter output unit is entered, the optimal equalizer parameters are configured, and if not, the operation is continued to the last group of optional equalizers.
The decoding unit is used for decoding the composite video signal and synchronizing each line signal of a frame, so that the automatic equalization method and the device can acquire stable signals.
Because the widths and the initial positions of the carrier synchronization edges of different systems are also different, the sampling module needs to count the synchronization edge information of multiple systems in advance, after the system judges the system information, different initial positions and data sampling numbers are configured to obtain effective falling edge data, and meanwhile, multi-line averaging can be selected for reducing the influence of signal noise.
The feature extraction unit performs feature calculation on the data of the synchronization edge. Specifically, due to the difference of the channel compensation strength under different equalizer parameters, the data waveform at the synchronous edge exhibits different rising states, as shown in fig. 4, which is the signal shape of the synchronous edge when the equalizer compensation strength under the long coaxial cable is from weak to strong. It can be seen that the larger the signal compensation intensity is, the faster the rising speed of the synchronous edge position is, but the too large compensation intensity will cause an "overshoot" state, as shown by P3 in fig. 4, and the waveform appears to rise to the highest position and then drop rapidly. Therefore, in this embodiment, based on the relationship between the rising speed of the sync edge and the stability of the subsequent signal and the strength of the equalizer, the embodiment proposes f1～f4The feature extraction strategy of (1).
Specifically, when a-b, c-d and g-h are selected, referring to fig. 4, the following strategies are adopted in the embodiment:
when each row of signals are synchronized, the central point o of the descending segment of the synchronizing edge is positioned; based on the point and the system information of the current decoding video, the position of the a point can be calibrated; the positions of points b, c, d, g and h are scaled based on the distance from point a on the data as shown in p 2. It should be noted that the same calibration information is required to be used for all three sections of positions in the same video format.
The parameter pre-screening unit firstly obtains a discrete equalizer configuration table by using a proper interpolation method based on the relation between a compensation frequency curve of the analog equalizer and parameter change, and the compensation strengths of the equalizer configuration table are sequentially arranged from small to large, so that the calculated characteristic vector can quickly reduce the search space of the equalizer parameters; then, carrying out feature vector calibration work on a system of a plurality of groups of coaxial cables with the lengths in the state that the equalizer is closed, wherein the process is carried out before the system formally runs; and finally, outputting the search index.
The optimal feature selection unit judges whether the compensation effect of the corresponding equalizer is good or bad according to the two groups of feature vectors, a feature discrimination model based on the equalization compensation effect is constructed in the embodiment, and f is established according to the signal fluctuation trend of the equalizer from small to large in compensation in the graph 41～f4The characteristic index is positively operated, so that the larger the transformed characteristic value is, the better the equalizer effect is; and finally outputting a judgment result.
Since the equalizer strength is continuously increased, the response value is increased to approach the optimal parameter and then decreased, so that the embodiment can stop the search in advance by the termination judging unit, which can reduce the time consumption and reduce the image distortion caused by excessive signal compensation from the image display.
In this embodiment, an adaptive channel equalization method is provided as follows:
firstly, feature data acquisition under typical configuration of an equalizer is carried out, 20 lengths of coaxial cables are respectively used for accessing a system, 25 groups of different parameters are configured for each length according to the compensation intensity of the equalizer from weak to strong, synchronous edge data sampling and feature extraction under each condition are completed, and 500 groups of feature vectors are obtained. Wherein the first set of parameters (20 sets in total) for each length is the use of the reference feature in the fast search mode. Performing principal component analysis on 500 groups of characteristics to obtain characteristic corresponding weight [ w1，w4，…，w4]. The process is an off-line step, and each system for simulating the equalizer only needs to be executed once, which is equivalent to the initial stepThe relationship of the equalized channel compensation to the eigenvector is determined.
Secondly, the system is electrified and decodes signals, 256 lines of synchronous edge signals of the same frame of picture are collected, and 350 sampling points are arranged on each line; and averaging sampling points at each position to obtain smoothed data.
Then, obtaining a feature vector based on the sampled data, and calculating the correlation degree with 20 groups of calibration features obtained offline to obtain an automatic equilibrium search space; initializing optimal parameters and feature vectors, and additionally configuring a first set of parameters in a search space.
And then, repeating the sampling step for 8 times under the same group of equalizer parameters to obtain 8 groups of data, carrying out feature extraction on the data, carrying out data verification, and carrying out the next step after the verification is successful.
And then, performing optimal feature selection by using the feature vector obtained in the previous step: and if the optimal characteristics are output from the previous step, updating the optimal balance parameters and the characteristic vectors, and if not, performing the next step.
And finally, performing difference judgment by using the output characteristics obtained in the previous step and the current optimal characteristics, stopping the automatic balancing device if the difference is overlarge, and continuously configuring the next group of equalizers to repeat the two steps if the difference is not overlarge.
It should be noted that the above three steps are iterative optimization processes, and the "current optimal feature" in the state where the apparatus is not finished is a local optimal feature when the current group is searched, and belongs to an intermediate result.
In addition to the above specific implementation method of adaptive channel equalization, this embodiment also provides another specific implementation method of adaptive channel equalization, which is as follows:
first, the system is powered on and decodes the signal, and 128 lines of synchronous edge signals of the same frame of picture are collected, and 350 sampling points are arranged on each line. And averaging sampling points at each position to obtain smoothed data.
And then, sequentially configuring the parameter configuration of the equalizer according to the compensation intensity from weak to strong, and skipping the parameter pre-screening process by using a default automatic equalization search space. It should be noted that the default auto-search space is based on equalizer configurable parameters. Different configuration combinations can obtain different frequency response curves. The principle of configuring the search space is that frequency response curves corresponding to different configurations can cover different compensation intensities of each frequency band.
And then, repeating the previous step for 3 times under the same group of equalizer parameters to obtain 3 groups of data, carrying out feature extraction on the data, sending the data to a feature verification module for data verification, and carrying out the next step after the verification is successful.
And finally, selecting the optimal feature by using the feature vector in the previous step. And if the optimal characteristics come from the current parameters, updating the optimal balance parameters and the characteristic vectors, and if not, carrying out the next step.
And finally, judging whether to stop the automatic balancing device or not according to the difference with the optimal characteristic, and otherwise, repeating the steps.
It should be noted that, in the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, similar parts between the embodiments may be referred to each other, and different parts between the embodiments may also be used in combination with each other, which is not limited by the present invention.
To sum up, the adaptive channel equalization method, apparatus, and computer storage medium for a coaxial video transmission system provided in this embodiment combine the feature extraction and determination of the channel compensation effect of the equalizer with the feature engineering, and provide a method for performing fast adaptive equalization using a limited equalizer coefficient search space to approximate full parameter search, and design an adaptive channel equalization method that uses the attenuation characteristic of the composite video signal itself and quickly selects the equalizer coefficient without depending on the pilot signal, so as to reduce the channel attenuation of the coaxial video transmission system, reduce the equalization time of the long-distance coaxial cable video transmission system, and increase the speed of displaying images, and improve the robustness of the equalization apparatus, thereby solving the problem of how to reduce the channel attenuation of the coaxial video transmission system, and how to reduce the equalization time, and how to perform fast adaptive equalization in the long-distance coaxial video transmission system, The speed of displaying images is increased and the robustness of the equalizing device is improved.
The above description is only for the purpose of describing the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention, and any variations and modifications made by those skilled in the art based on the above disclosure are within the scope of the appended claims.
Claims (13)
1. An adaptive channel equalization method for a coaxial video transmission system, the adaptive channel equalization method comprising:
s1, receiving a composite video signal, the composite video signal consisting of a sync edge signal, a chrominance composite video signal and a valid data signal;
s2, decoding the composite video signal;
s3, sampling the synchronous edge signal in the decoded composite video signal to obtain synchronous edge data;
s4, extracting the features of the synchronous edge data to obtain a feature vector;
s5, when the equalizer is in a closed state, calibrating the characteristic vector;
s6, repeating S2-S3 n times, wherein n is more than or equal to 2;
s7, checking the feature vector to judge whether the feature vector meets the selection requirement: if the selection requirement is met, the verification is successful, otherwise, the S2 is repeated;
s8, judging the compensation effect of the equalizer according to the two groups of characteristic vectors and outputting the locally optimal equalizer parameters;
and S9, judging whether the automatic equalization stops: if the decision is stopped, the optimal equalizer parameters are configured, otherwise, the next set of equalizer parameters is configured and the process returns to S2.
2. The adaptive channel equalization method for a coaxial video transmission system according to claim 1, wherein S3 comprises:
counting the synchronous edge information of various systems to form a synchronous edge information base;
obtaining current system information under the state that the equalizer is closed,then decoding the signal, obtaining the synchronous edge width and the initial position of the corresponding system from the synchronous edge information base, sampling the synchronous edge area data, and recording as
Wherein n represents the number of sampling points, and the superscript 0 represents that the equalizer is in a closed state;
and comparing the synchronous edge data obtained by sampling with the synchronous edge information in the synchronous edge information base to obtain the system information of the synchronous edge data.
3. The adaptive channel equalization method for a coaxial video transmission system according to claim 1, wherein S4 comprises:
selecting the rising segments a-b of the synchronous edge signals and extracting a trend characteristic f from the rising segments1；
Selecting attenuation sections c-d of the synchronous edge signals and extracting trend characteristics f from the attenuation sections2；
Extracting curvature radius characteristic f from attenuation section c-d of synchronous edge signal3；
Selecting a stationary section g-h of the synchronous edge signal, and extracting a volatility characteristic f from the stationary section g-h4；
The feature vector is denoted as f1，f2，f3，f4}。
4. The adaptive channel equalization method for coaxial video transmission system according to claim 3, wherein the trend feature f is extracted1The method comprises the following steps:
obtaining a difference sequence [ Delta S ] of the synchronization edge signala＝Sa+1-Sa，…，ΔSb-1＝Sb-Sb-1}；
Maximum point r in differential sequence1The differential value of (d) is noted as:
ΔSr1＝max({ΔSa，ΔSa+1，...，ΔSb-1})；
to a point r1And p on the left and right1The points are fitted by using a least square method, and the first derivative is taken as a trend characteristic f1：
5. The adaptive channel equalization method for coaxial video transmission system according to claim 4, wherein the trend feature f is extracted2The method comprises the following steps:
obtaining a sequence of signal differences, { Δ S }c＝Sc+1-Sc，…，ΔSd-1＝Sd-Sd-1}；
Maximum point r in differential sequence2The differential value of (d) is noted as:
ΔSr2＝max({ΔSc，ΔSc+1，…，ΔSd-1})；
to a point r2And p on the left and right2The points are fitted by using a least square method, and the first derivative is taken as a trend characteristic f2：
6. The adaptive channel equalization method for coaxial video transmission system according to claim 5, wherein the curvature radius feature f is extracted3The method comprises the following steps:
calculating a second order difference sequence [ Delta ]2Sc＝ΔSc+1-ΔSc，…，Δ2Sd-2＝ΔSd-1-ΔSd-2}；
Minimum point r in second order difference3The differential value of (d) is given as:
Δ2Sr3＝min({Δ2Sc，Δ2Sc+1，…，Δ2Sd-2})；
to a point r3And p on the left and right3The points are fitted using a least squares method to obtain a first order difference sequence:
in a first order difference sequence, point r3And p on the left and right4The slope of the straight line fitted to a point is approximated as the second derivative of that point:
calculating the point r3The radius of curvature is the radius of curvature characteristic f3：
7. The adaptive channel equalization method for coaxial video transmission system according to claim 6, wherein the fluctuation characteristic f is extracted4The method comprises the following steps:
under the condition of no interference, setting the average value of the signals close to the h point to be approximately equal to the average value of the whole data;
obtaining p around h point5Mean of points
Characteristic of fluctuation f4Is { Sg，Sg+1，…，ShRelative to
Sum of squared average errors of:
8. the adaptive channel equalization method for coaxial video transmission system according to claim 7, wherein said equalizer comprises discrete m equalizers { q }1，q2，...，qmThe m equalizers are obtained by using a proper interpolation method based on the relation between a compensation frequency curve of the analog equalizer and parameter change;
s5 includes:
when the equalizer is in a closed state, the calculated eigenvector value is taken
Wherein j is 1,2,3, 4;
let u set of reference features { F1，F2，…，FuAnd k sets of search start indices I1，I2，…，IkAnd (c) the step of (c) in which,
a feature vector representing the i-th set of calibrations, i ═ 1,2, … …, u;
calculating each group of calibration characteristics and F in sequence0Absolute difference of (2)
Let all Δ F0iMinimum value of is δ1＝min{ΔF0iAt maximum value δ2＝max{ΔF0iAnd define FiAnd F0Correlation coefficient of j-th feature
Where ρ isRepresents a resolution coefficient;
calculating each set of calibration features and F0Degree of association of
Output search index w ═ Imin(r0i)。
9. The adaptive channel equalization method for a coaxial video transmission system according to claim 8, wherein S7 comprises:
let t-group characteristics of w-th group equalizer output be
For the trend feature f1Trend characteristic f2Radius of curvature characteristic f3And a volatility characteristic f4And (3) checking independently: let the variance
Wherein
The mean value is represented by the average value,
j represents the j-th characteristic value of the i-th repeated test, j is 1, …, 4;
calculating a verification threshold T for a feature jj: under the condition that the confidence coefficient is 95%, the critical value of t times of verification is recorded as v (t), and then
If sigma (j)>TjThen the verification of the feature j is failed.
10. The adaptive channel equalization method for a coaxial video transmission system according to claim 9, wherein S8 comprises:
establishing a trend feature f1Trend characteristic f2Radius of curvature characteristic f3And a volatility characteristic f4To obtain the changed trend characteristics
Trend characteristics
Radius of curvature feature
And wave characteristics
Wherein f is1bestThe trend characteristic f1 is taken when the equalization effect is the best;
confirming changed trend characteristic trend characteristics by using principal component analysis method
Trend characteristics
Radius of curvature feature
And wave characteristics
Weight in decision hierarchy [ w ]1，w2，…，w4]；
Calculating a response value
And selecting the maximum response value as the locally optimal equalizer parameter output.
11. The adaptive channel equalization method for a coaxial video transmission system according to claim 10, wherein S9 comprises:
according to the c group equalizer qcResponse value of
And an optimal equalizer qbResponse value of
Whether or not to stop the automatic equalization in advance is judged.
12. An adaptive channel equalization apparatus of a coaxial video transmission system for implementing the adaptive channel equalization method of the coaxial video transmission system according to any one of claims 1 to 11, wherein the adaptive channel equalization apparatus comprises a coaxial video signal processor and an equalizer;
the coaxial video signal processor comprises a decoding unit and a sampling unit; the decoding unit is used for decoding a video signal so as to synchronize each line of signals of the video signal; the sampling unit is used for acquiring all synchronous edge data in the decoded video signal when the equalizer is in a closed state;
the equalizer comprises a feature extraction unit, a parameter pre-screening unit, a feature verification unit, an optimal feature selection unit, a termination judgment unit and a parameter output unit; the feature extraction unit is used for performing feature calculation on the synchronous edge data to obtain a feature vector; the parameter pre-screening unit is pre-stored with a plurality of equalizer parameters and is used for calibrating the characteristic vector when the equalizer is in a closed state; the characteristic checking unit is used for checking the characteristic vector to judge whether the characteristic vector meets the selection requirement; the optimal feature selection unit is used for judging the compensation effect of the equalizer according to the two groups of feature vectors; the termination judging unit is used for judging whether to stop the automatic balancing strategy or not; the parameter output unit is used for outputting the parameters of the equalizer with the optimal compensation effect.
13. A computer storage medium, having a computer program stored thereon, which, when being executed by a processor, implements the adaptive channel equalization method for a coaxial video transmission system according to any one of claims 1 to 11.
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