CN106572093B - A kind of wireless sensor array data compression method and system - Google Patents
A kind of wireless sensor array data compression method and system Download PDFInfo
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- CN106572093B CN106572093B CN201610930928.9A CN201610930928A CN106572093B CN 106572093 B CN106572093 B CN 106572093B CN 201610930928 A CN201610930928 A CN 201610930928A CN 106572093 B CN106572093 B CN 106572093B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/04—Protocols for data compression, e.g. ROHC
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/17—Function evaluation by approximation methods, e.g. inter- or extrapolation, smoothing, least mean square method
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/17—Function evaluation by approximation methods, e.g. inter- or extrapolation, smoothing, least mean square method
- G06F17/175—Function evaluation by approximation methods, e.g. inter- or extrapolation, smoothing, least mean square method of multidimensional data
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
- H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
- H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
- H03M7/40—Conversion to or from variable length codes, e.g. Shannon-Fano code, Huffman code, Morse code
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Abstract
The present invention provides a kind of wireless sensor array data compression method and system, and the data volume of transmission can be effectively reduced under degree of precision, to reduce transmission cost, while can guarantee the reliability of data.The described method includes: in transmitting terminal, using spline curve fitting original sensor array data, the optimum control vector of spline interpolation expression formula when obtaining making the match value error minimum of the original sensor array data and the original sensor array data；According to the obtained optimum control vector reconstruction spline curve, the match value of the original sensor array data is obtained；Calculate the error between the original sensor array data and the match value of the original sensor array data and quantization；Huffman encoding is carried out to the error after quantization, coding result and the optimum control vector are sent to receiving end.The present invention is suitable for technical field of data compression.
Description
Technical field
The present invention relates to technical field of data compression, particularly relates to a kind of wireless sensor array data compression method and be
System.
Background technique
With microelectric technique and MEMS (MEMS, Micro-Electro-Mechanical System) technology
Continuous progress also obtained tremendous development as the most basic and most important sensor of acquisition of information.Sensor array is exactly
Formed by being deployed in a large amount of microsensor node (for example, wireless sensor node) in special geological surrounding, such as to
It collects hydrographic data and disposes underwater sensor array.Since geographical environment is restricted, wireless sensor node is generally logical
It crosses communication and carries out information transmission, achieve the purpose that perception, acquisition monitor the information for being perceived object in region.
By taking wireless sense network environmental monitoring system as an example, wireless sense network environmental monitoring system passes through portion within a certain area
It affixes one's name to a large amount of wireless sensor nodes and long term monitoring is carried out to the regional environment.The sensing unit of wireless sensor node is to perception
Environmental information is acquired, and processing unit stores and processs the data of itself acquisition, finally carries out information biography by communication unit
It is defeated.If carrying out the monitoring of three-dimensional space geographical environment, such as monitoring to waters, soil, such sensor node cannot
Comprehensively, information is completely collected.Generally the single sensor on wireless sensor node is expanded as sensor array.Sensor
Array is exactly to be made of one group of sensor for being deployed in special geological surrounding in special geometric distribution.For example, by sensor array
It is linear to dispose region under water, the hydrographic datas such as flow velocity, direction, the salinity of different depth can be collected, as shown in Figure 1
Wireless sense network hydrologic monitoring system.Sensor array, which is listed in each sampling instant, can acquire one group of new sensor array columns
According to a large amount of sensor array data needs are transferred to data center in time under conditions of guaranteeing certain precision to serve phase
Close application.Due to wireless sensor node often apart from base station farther out, mostly transmit data to data center using satellite, therefore big
It measures frequent long range wireless data transmission and brings huge energy expense and communication cost.
Data compression refers under the premise of not losing useful information, reduces data volume to reduce memory space, improves it
Transmission, storage and processing efficiency, or data are reorganized according to certain algorithm, reduce the redundancy and storage of data
A kind of technical method in space.Lossless compression is compressed using the statistical redundancy of data, can completely restore initial data,
Compression ratio is generally relatively low.Compression method allows to lose certain information during compressing, although cannot restore completely
Initial data, but the part lost is smaller to the influence for understanding initial data, has but brought relatively high compression ratio.
Huffman (Huffman) coding is a kind of typical lossless compression method, by by the biggish symbol of probability of occurrence
It is indicated with the shorter code word of word length, the lesser symbol of probability of occurrence is indicated to realize compression with the longer code word of word length.It is encoding
It requires when with decoding according to the code book for having recorded symbol Yu code word corresponding relationship.The probability really occurred when symbol and life
At the symbol appearing probability that uses of code book it is consistent when, the compression effectiveness of Huffman coding is very good.If sensor array columns
Regard a vector as according to whole, code book very can be not easy to be stored in the memory of wireless sensor node greatly；If sensing
Device array data regards the set being made of single sensing data scalar as and can ignore the association between adjacent sensors.
Adaptive segmentation constant approximate (APCA, adaptive piecewise constant approximation) is
A kind of compression method for time series also can be applied in the spatial sequence data of sensor array generation.
APCA method has ignored a certain range of data fluctuations.When the error of mark position value and present position values has reached setting
As soon as can be divided into independent section when thresholding, this section is indicated with this constant of mark position value.But this method compression ratio is higher
When, error can be very big, and precision is always difficult to weigh between compression ratio and precision by extreme influence.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of wireless sensor array data compression method and systems, with solution
Certainly the coding of Huffman present in the prior art is not suitable for the application scenarios of sensor array data, adaptive segmentation constant
Approximation method not can guarantee the problem of reliability of data.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of wireless sensor array data compression method, packet
It includes:
In transmitting terminal, using spline curve fitting original sensor array data, obtain making the original sensor array
The optimum control vector of spline interpolation expression formula when the match value error minimum of data and the original sensor array data；
According to the obtained optimum control vector reconstruction spline curve, the quasi- of the original sensor array data is obtained
Conjunction value；
Calculate the error between the original sensor array data and the match value of the original sensor array data
And quantify；
Huffman encoding is carried out to the error after quantization, coding result and the optimum control vector are sent to reception
End.
Further, the optimum control vector representation are as follows:
Wherein,Indicate optimum control vector, A+Indicate that the generalized inverse matrix of A, A indicate the interpolation coefficient square of spline curve
Battle array, Y indicate the original sensor array data.
Further, the optimum control vector reconstruction spline curve that the basis obtains, obtains the raw sensory
The match value of device array data includes:
The obtained optimum control vector is quantified；
According to the optimum control vector reconstruction spline curve after quantization；
According to the spline curve of reconstruct, the match value of the original sensor array data is obtained；
Wherein, the match value of the original sensor array data indicates are as follows: Indicate original sensor array
The match value of data, A indicate the interpolation coefficient matrix of spline curve,Indicate optimum control vector.
Further, the error after described pair of quantization carries out Huffman encoding, and coding result and the optimum control are sweared
Amount is sent to receiving end and includes:
Huffman encoding is carried out to the error after quantization；
Coding result and the optimum control vector are constituted into data packet；
The data packet of composition is sent to receiving end.
Further, the method also includes:
In receiving end, the data packet being made of coding result and the optimum control vector is received；
According to the optimum control vector reconstruction spline curve in the data packet received, the raw sensor is obtained
The match value of array data；
Hafman decoding is carried out to the coding result in the data packet received；
The match value of the original sensor array data is added with decoding result, obtains the sensor array decompressed out
Column data.
The embodiment of the present invention also provides a kind of wireless sensor array data compression system, comprising:
First determining module, for using spline curve fitting original sensor array data, obtaining making institute in transmitting terminal
Spline interpolation when stating match value error minimum of the original sensor array data with the original sensor array data is expressed
The optimum control vector of formula；
Second determining module, for obtaining described original according to the obtained optimum control vector reconstruction spline curve
The match value of sensor array data；
Third determining module, for calculating the original sensor array data and the original sensor array data
Error and quantization between match value；
Sending module is encoded, for carrying out Huffman encoding to the error after quantization, by coding result and the optimal control
Vector processed is sent to receiving end.
Further, the optimum control vector representation are as follows:
Wherein,Indicate optimum control vector, A+Indicate that the generalized inverse matrix of A, A indicate the interpolation coefficient square of spline curve
Battle array, Y indicate the original sensor array data.
Further, second determining module includes:
Quantifying unit, for quantifying to the obtained optimum control vector；
Reconfiguration unit, for according to the optimum control vector reconstruction spline curve after quantization；
Determination unit obtains the match value of the original sensor array data for the spline curve according to reconstruct；
Wherein, the match value of the original sensor array data indicates are as follows: Indicate original sensor array
The match value of data, A indicate the interpolation coefficient matrix of spline curve,Indicate optimum control vector.
Further, the coding sending module includes:
Coding unit, for carrying out Huffman encoding to the error after quantization；
Component units, for coding result and the optimum control vector to be constituted data packet；
Transmission unit, for the data packet of composition to be sent to receiving end.
Further, the system also includes:
Receiving module, for receiving the data packet being made of coding result and the optimum control vector in receiving end；
4th determining module, the optimum control vector reconstruction spline curve in the data packet received for basis,
Obtain the match value of the original sensor array data；
Decoder module, for carrying out Hafman decoding to the coding result in the data packet received；
5th determining module is obtained for the match value of the original sensor array data to be added with decoding result
The sensor array data decompressed out.
The advantageous effects of the above technical solutions of the present invention are as follows:
In above scheme, in transmitting terminal, using spline curve fitting original sensor array data, obtain making described original
Spline interpolation expression formula when the match value error minimum of sensor array data and the original sensor array data is most
Excellent control vector；According to the obtained optimum control vector reconstruction spline curve, the original sensor array data are obtained
Match value；Calculate the error between the original sensor array data and the match value of the original sensor array data
And quantify；Huffman encoding is carried out to the error after quantization, coding result and the optimum control vector are sent to receiving end.
In this way, by using the spline curve fitting original sensor array data with high compression rate and with high encoding precision
Huffman coding Mixing compression algorithm, the data volume of transmission can be effectively reduced under degree of precision, with reduce transmission at
This, while can guarantee the reliability of data.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of wireless sense network hydrologic monitoring system provided in an embodiment of the present invention；
Fig. 2 is the flow diagram of wireless sensor array data compression method provided in an embodiment of the present invention；
Fig. 3 indicates original sensor array data using Catmull-Rom spline curve to be provided in an embodiment of the present invention
Schematic diagram；
Fig. 4 is control point p provided in an embodiment of the present inventioni-1,pi,pi+1And pi+2Position view；
Fig. 5 is dummy control point schematic diagram provided in an embodiment of the present invention；
Fig. 6 is the idiographic flow schematic diagram of wireless sensor array data compression method provided in an embodiment of the present invention；
Fig. 7 be direct quantization provided in an embodiment of the present invention, tri- kinds of compression algorithms of APCA, CSA pack arrangement schematic diagram；
Fig. 8 is the distribution schematic diagram of error provided in an embodiment of the present invention；
Fig. 9 is E provided in an embodiment of the present inventionmaxWhen=8, size of data schematic diagram after compression；
Figure 10 is E provided in an embodiment of the present inventionmaxWhen=32, the schematic diagram of size of data after compression；
Figure 11 is the structural schematic diagram of wireless sensor array data compression system provided in an embodiment of the present invention.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail.
The present invention is not suitable for the application scenarios of sensor array data for existing Huffman coding, adaptive to divide
Section constant approximation method the problem of not can guarantee the reliability of data, provide a kind of wireless sensor array data compression method and
System.
Embodiment one
Referring to shown in Fig. 2, wireless sensor array data compression method provided in an embodiment of the present invention, comprising:
S101, using spline curve fitting original sensor array data, obtains making the raw sensor in transmitting terminal
The optimum control of spline interpolation expression formula when the match value error minimum of array data and the original sensor array data
Vector；
S102 obtains the original sensor array number according to the obtained optimum control vector reconstruction spline curve
According to match value；
S103 is calculated between the original sensor array data and the match value of the original sensor array data
Error simultaneously quantifies；
S104 carries out Huffman encoding to the error after quantization, coding result and the optimum control vector is sent to
Receiving end.
Wireless sensor array data compression method described in the embodiment of the present invention, it is quasi- using spline curve in transmitting terminal
Original sensor array data are closed, obtain making the quasi- of the original sensor array data and the original sensor array data
The optimum control vector of spline interpolation expression formula when conjunction value error minimum；According to the obtained optimum control vector reconstruction sample
Curve, obtains the match value of the original sensor array data；Calculate the original sensor array data and the original
Error and quantization between the match value of beginning sensor array data；Huffman encoding is carried out to the error after quantization, will be encoded
As a result receiving end is sent to the optimum control vector.In this way, former by using the spline curve fitting with high compression rate
The Mixing compression algorithm of beginning sensor array data and the Huffman coding with high encoding precision, can be under degree of precision
The data volume of transmission is effectively reduced, to reduce transmission cost, while can guarantee the reliability of data.
In the present embodiment, using the spline curve fitting original sensor array data with high compression rate and there is high compile
The Mixing compression algorithm of the Huffman coding of code precision, can effectively avoid that spline curve fitting method compression ratio is used alone
High and disadvantage and exclusive use Huffman coding that precision the is inadequate excessive application for not being suitable for sensor array data of code book
The problem of scene.
In the present embodiment, it is assumed that have N number of sensor on an array of sensors, N number of sensor is denoted as S1,S2,...,SN, N number of
Sensor is deployed at equal intervals from x1To xNDepth bounds in, then being divided into (x between sensorN-x1)/(N-1)。
In some specific sampling instant, sensor SiCollected data are yi, in order to indicate entire sensor array data, define N
Column vector Y is tieed up, Y is expressed as formula (1):
Y=[y1,y2,...,yN]T (1)
In formula (1), Y indicates sensor array S1,S2,...,SNIn the collected sensor array columns of a certain sampling instant
According to, Y is referred to as original sensor array data,TIndicate transposition.
In the present embodiment, can use Catmull-Rom spline curve as accurately as possible will be original using a small amount of numerical value
Sensor array data Y is expressed, as shown in Figure 3, wherein p1,p2,...,pMControl point is represented, spline curve control point
Number shares M, and i-th of control point is denoted as pi, p is remembered at control pointiIt can be indicated with a two-dimensional columns vectorIts
In, 1≤i≤M, that is, is located at control point p by i-th section on curveiAnd pi+1Between one section, can be calculated by four control points
Come, i.e. pi-1,pi,pi+1And pi+2, as shown in Figure 4.Based on the wireless biography of Catmull-Rom spline curve described in the present embodiment
Sensor array data compression method is alternatively referred to as based on Catmull-Rom spline approxmation (CSA, Catmull-Rom spline
Approximation the compression method of wireless sensor array data).
In the present embodiment, if control point position is spacedly distributed in x-axis, then control point piPosition p in x-axisi x
It can be expressed as formula (2):
It follows that Catmull-Rom spline curve has been divided into M-1 sections by control point, point is in x-axis in i-th of segmentation
Position meetSince Catmull-Rom spline curve has continuity, so waypoint is divided into left section also
Being right section does not influence.
By the value at control pointThe M dimensional vector of composition is denoted as B, then B can be expressed as formula (3):
In other words, B is the control vector of Catmull-Rom spline curve.
For the first section and endpiece of Catmull-Rom batten, since no preposition control point and subsequent control point cannot be into
Row data interpolating is its dummy two additional control point, as shown in figure 5, dummy control point meets formula (4):
If j-th of sensor belongs to the kth of Catmull-Rom spline curvejSection, can obtain kjMeet formula (5):
It, can be according to the variable coefficient parameter { b of Catmull-Rom spline curve in the present embodimentiReconstruct spline curve.
If sensor SjBelong to the kth of spline curvejSection, then the interpolation parameter of Catmull-Rom spline interpolation expression formula can indicate
For formula (6):
In formula (6), tjThe interpolation parameter for indicating j-th of sensor, also illustrates that xjIn kthjRelative position in section；xjTable
Show the position of j-th of sensor；Indicate kthjPosition of a control point in x-axis,Indicate kthj+1A control point is in x
Position on axis, kthjThe both ends of section are control pointsThe control point and
In the present embodiment, the Catmull-Rom spline curve is a kind of C1Continuous cubic spline curve, therefore,
Catmull-Rom spline interpolation formula can be expressed as multinomial p (t)=c0+c1+c2t2+c3t3, wherein c0、c1、c2、c3Table
The interpolation parameter for showing polynomial coefficient, t representative polynomial, t is normalized between 0-1.
As shown in figure 4, multinomial p (t)=c0+c1+c2t2+c3t3Constraint condition are as follows:
P (0)=pi
P (1)=pi+1
According to multinomial p (t)=c0+c1+c2t2+c3t3With multinomial p (t)=c0+c1+c2t2+c3t3Constraint condition, can
Obtain Catmull-Rom spline interpolation formula:
In formula (7), pi-1,pi,pi+1And pi+2Indicate control point.
According to formula (7), can be obtained in xjThe match value at placeAre as follows:
In formula (8), tjThe interpolation parameter for indicating j-th of sensor, also illustrates that xjIn kthjRelative position in section, such as Fig. 4
Shown, four control points of every section of needs are calculated, 4 control parameters of every section of needs,It indicates
KthjThe corresponding control parameter of section.
According to formula (8), if defining aj,iFor
In formula (9), aj,iIt indicates to be located at the value that interpolation coefficient matrix jth row i-th arranges；Formula (9) is illustrated with general formula
The interpolation coefficient that any one section of Catmull-Rom spline curve.
It is available according to formula (8) and formula (9)
Further, formula (10) can be of equal value are as follows:
In formula (11), B indicates the control vector of Catmull-Rom spline curve, and the element in B is control parameter, that is, controls
The value of point is made, A indicates the interpolation coefficient matrix of Catmull-Rom spline curve,Indicate the quasi- of original sensor array data
Conjunction value.
Formula (11) also may indicate that are as follows:
In formula (11), A can be indicated are as follows:
A=[aj,i]N×M (13)
Being intended to ask indicates that the optimum control vector of Catmull-Rom spline curve makes the original sensor array data Y
With match valueError is minimum, it may be assumed that
If the generalized inverse matrix of matrix A is A+, then optimum control vectorI.e. are as follows:
Since matrix A and matrix Y are mutually indepedent, matrix A+It can calculate and store in advance, be won conveniently for subsequent calculating.
In the present embodiment, to the obtained optimum control vectorQuantified, according to the optimum control vector after quantization
Reconstruct spline curve；According to the spline curve of reconstruct, the match value of the original sensor array data is obtained, wherein described
The match value of original sensor array data are as follows:
In the present embodiment, the match value based on Catmull-Rom spline curve remains original sensor array data
Main trend, especially when control point is reduced, error can not just be had ignored.Then it also needs to encode error, because
Wireless sensor array data compression method described in this present embodiment is a kind of mixed compression algorithm.Remember the raw sensory
Error between device array data and the match value of the original sensor array data are as follows:
Error delta is quantified, be denoted as Δ '.Using Huffman coding to the result Δ after quantization ' progress Huffman
Coding, is denoted as E, and coding result E and the optimum control vector are constituted data packet；The data packet of composition is sent to reception
End；Wherein, the code book of Huffman coding can calculate in advance according to historical data.
In the present embodiment, the wireless sensor array data compression method is compressed through this embodiment most terminates
Fruit can indicate are as follows:
As shown in fig. 6, in the present embodiment, the compression method of the wireless sensor array data based on CSA is needed in transmitting terminal
To pass through following 6 steps:
Step1: Catmall-Rom spline curve fitting original sensor array data are utilized, obtain making the original biography
The optimum control vector of spline interpolation expression formula when sensor array data and match value error minimum
Step2: to obtained optimum control vectorQuantified；
Step3: optimum control vector is utilizedCatmall-Rom spline curve is reconstructed, the original sensor array is obtained
The match value of data
Step4: it calculates between original sensor array data and the match value of the original sensor array data
Error simultaneously quantifies；
Step5: carrying out Huffman to the quantized result of Step4 and encode to obtain E, willData packet is constituted with E；
Step6: send byThe data packet constituted with E is to receiving end.
In the specific embodiment of aforementioned wireless sensor array data compression system, further, the method is also
Include:
In receiving end, the data packet being made of coding result and the optimum control vector is received；
According to the optimum control vector reconstruction spline curve in the data packet received, the raw sensor is obtained
The match value of array data；
Hafman decoding is carried out to the coding result in the data packet received；
The match value of the original sensor array data is added with decoding result, obtains the sensor array decompressed out
Column data.
As shown in fig. 6, in the present embodiment, the compression method of the wireless sensor array data based on CSA is needed in receiving end
To pass through following 4 steps:
Step1: receive byThe data packet constituted with E；
Step2: according to the optimum control vector in the data packet receivedCatmall-Rom spline curve is reconstructed, is obtained
The match value of the original sensor array data
Step3: Huffman decoding is carried out to the E in the data packet received；
Step4: by the match value of the original sensor array dataIt is added with the Huffman decoding result of Step4,
Obtain the sensor array data Y' decompressed out.
In order to verify the wireless sensor array data described in the present embodiment based on CSA compression method validity,
By the compression method (abbreviation CSA compression algorithm) of the wireless sensor array data described in the present embodiment based on CSA and directly
Two kinds of quantization, APCA Lossy Compression Algorithms compare, and the corresponding pack arrangement of three kinds of algorithms is as shown in Figure 7.
Three kinds of compression algorithms are using the collected actual sensor array data in Qinhuangdao harbour as compressed object.Given one
A sensor array with 15 sensors, i.e. N=15.Flow velocity of the sensor to collect different depth water, data are dilute
It is distributed in -4096 thinly between 4096mm/s, that is, needs 13bits that could indicate.So each one sensor of sampling instant
The data volume that array generates is 13 × 15=195bits.By CSA compression algorithm emulation it has also been found that, error range -600 to
Between 600mm/s, wherein having 70% to be confined to -128 between 128mm/s, distribution is as shown in Figure 8.According to the distribution of error
It is found that the Huffman coding in CSA compression algorithm will be highly effective, code book also very little is encoded.
Directly quantization is a kind of basic compression method.Assuming that worst error thresholding Emax=8, it is denoted as Q-8, that is, is measured
Changing step-length is 16, then indicating that the data of a sensor need 9bits.Therefore one sensor array of a sampling instant produces
Raw data volume is 9 × 15=135bits.Similarly, worst error thresholding Emax=16, it is denoted as Q-16, data volume 120bits.
A kind of limited Lossy Compression Algorithm of error of APCA algorithm.In the algorithm compressed data can with (x, y) this
The value (the collected data of sensor) of the array representation that sample occurs in pairs, the i.e. position of sensor and sensor.Sensor
Position needs 4bits to indicate, the value of sensor needs 13bits to indicate.The number K of data pair needs 4bits.Remember APCA-
8 take 8, i.e. E for the worst error thresholding of APCA algorithmmax=8.It can similarly obtain, APCA-16 Emax=16.
The compressed data of CSA compression algorithm mainly there are two part, determine for expression Catmull-Rom batten by a part
Long parameter, another part are the elongated data for indicating error.The number at control point is set as 4, the step-length of quantization fixed length parameter is
64, then the total amount of data of fixed length argument section is 28bits after quantization.The worst error thresholding of CSA compression algorithm depends on table
The quantization step for showing the elongated data of error, the step-length for quantifying elongated parameter is 16, then worst error thresholding is Emax=8, note
For CSA-8.It can similarly obtain, CSA-16 Emax=16.
It is compressed using the data that different compression algorithms acquire 100 sampling instants, worst error thresholding is respectively 8
With 32, as a result as shown in Figure 9, Figure 10.It is as shown in the table to count compression ratio.
The compression ratio of the different compression algorithms of table 1
| Compression algorithm | Size of data (bit) | Relative size |
| Initial data | 195 | 100 |
| APCA-8 | 238.2 | 122.2 |
| Q-8 | 135 | 69.2 |
| CSA-8 | 114.4 | 58.7 |
| APCA-32 | 192.6 | 98.8 |
| Q-32 | 105 | 53.9 |
| CSA-32 | 77.4 | 39.7 |
Experimental result is it is found that CSA compression algorithm has some superiority with respect to other algorithms, in EmaxOriginal is compressed to when=8
58.7% come, in EmaxOriginal 39.7% is compressed to when=32.The compression effectiveness of CSA compression algorithm is than directly quantifying
Method well at least 10%, than APCA compression algorithm at least 60%.
Embodiment two
The present invention also provides a kind of specific embodiments of wireless sensor array data compression system, since the present invention mentions
The specific embodiment of the wireless sensor array data compression system of confession and aforementioned wireless sensor array data compression method
Corresponding, which can be walked by the process executed in above method specific embodiment
It is rapid to achieve the object of the present invention, therefore explaining in above-mentioned wireless sensor array data compression method specific embodiment
It is bright, it is also applied for the specific embodiment of wireless sensor array data compression system provided by the invention, below the present invention
Specific embodiment in will not be described in great detail.
Referring to shown in Figure 11, the embodiment of the present invention also provides a kind of wireless sensor array data compression system, comprising:
First determining module 11, for being made in transmitting terminal using spline curve fitting original sensor array data
Spline interpolation table when the match value error minimum of the original sensor array data and the original sensor array data
Up to the optimum control vector of formula；
Second determining module 12, for obtaining the original according to the obtained optimum control vector reconstruction spline curve
The match value of beginning sensor array data；
Third determining module 13, for calculating the original sensor array data and the original sensor array data
Match value between error and quantization；
Sending module 14 is encoded, for carrying out Huffman encoding to the error after quantization, by coding result and described optimal
Control vector is sent to receiving end.
Wireless sensor array data compression system described in the embodiment of the present invention, it is quasi- using spline curve in transmitting terminal
Original sensor array data are closed, obtain making the quasi- of the original sensor array data and the original sensor array data
The optimum control vector of spline interpolation expression formula when conjunction value error minimum；According to the obtained optimum control vector reconstruction sample
Curve, obtains the match value of the original sensor array data；Calculate the original sensor array data and the original
Error and quantization between the match value of beginning sensor array data；Huffman encoding is carried out to the error after quantization, will be encoded
As a result receiving end is sent to the optimum control vector.In this way, former by using the spline curve fitting with high compression rate
The Mixing compression algorithm of beginning sensor array data and the Huffman coding with high encoding precision, can be under degree of precision
The data volume of transmission is effectively reduced, to reduce transmission cost, while can guarantee the reliability of data.
In the specific embodiment of aforementioned wireless sensor array data compression system, further, the optimal control
Vector representation processed are as follows:
Wherein,Indicate optimum control vector, A+Indicate that the generalized inverse matrix of A, A indicate the interpolation coefficient square of spline curve
Battle array, Y indicate the original sensor array data.
In the specific embodiment of aforementioned wireless sensor array data compression system, further, described second really
Cover half block includes:
Quantifying unit, for quantifying to the obtained optimum control vector；
Reconfiguration unit, for according to the optimum control vector reconstruction spline curve after quantization；
Determination unit obtains the match value of the original sensor array data for the spline curve according to reconstruct；
Wherein, the match value of the original sensor array data indicates are as follows: Indicate original sensor array
The match value of data, A indicate the interpolation coefficient matrix of spline curve,Indicate optimum control vector.
In the specific embodiment of aforementioned wireless sensor array data compression system, further, the coding hair
The module is sent to include:
Coding unit, for carrying out Huffman encoding to the error after quantization；
Component units, for coding result and the optimum control vector to be constituted data packet；
Transmission unit, for the data packet of composition to be sent to receiving end.
In the specific embodiment of aforementioned wireless sensor array data compression system, further, the system is also
Include:
Receiving module, for receiving the data packet being made of coding result and the optimum control vector in receiving end；
4th determining module, the optimum control vector reconstruction spline curve in the data packet received for basis,
Obtain the match value of the original sensor array data；
Decoder module, for carrying out Hafman decoding to the coding result in the data packet received；
5th determining module is obtained for the match value of the original sensor array data to be added with decoding result
The sensor array data decompressed out.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, it can also make several improvements and retouch, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of wireless sensor array data compression method characterized by comprising
In transmitting terminal, using spline curve fitting original sensor array data, obtain making the original sensor array data
With the optimum control vector of the spline interpolation expression formula when match value error minimums of the original sensor array data；
According to the obtained optimum control vector reconstruction spline curve, the fitting of the original sensor array data is obtained
Value；
Calculate the error and amount between the original sensor array data and the match value of the original sensor array data
Change；
Huffman encoding is carried out to the error after quantization, coding result and the optimum control vector are sent to receiving end.
2. wireless sensor array data compression method according to claim 1, which is characterized in that the optimum control arrow
Amount is expressed as:
Wherein,Indicate optimum control vector, A+Indicate that the generalized inverse matrix of A, A indicate the interpolation coefficient matrix of spline curve, Y
Indicate the original sensor array data.
3. wireless sensor array data compression method according to claim 1, which is characterized in that the basis obtained
The optimum control vector reconstruction spline curve, the match value for obtaining the original sensor array data include:
The obtained optimum control vector is quantified；
According to the optimum control vector reconstruction spline curve after quantization；
According to the spline curve of reconstruct, the match value of the original sensor array data is obtained；
Wherein, the match value of the original sensor array data indicates are as follows: Indicate original sensor array data
Match value, A indicate spline curve interpolation coefficient matrix,Indicate optimum control vector.
4. wireless sensor array data compression method according to claim 1, which is characterized in that after described pair of quantization
Error carries out Huffman encoding, and coding result and the optimum control vector, which are sent to receiving end, includes:
Huffman encoding is carried out to the error after quantization；
Coding result and the optimum control vector are constituted into data packet；
The data packet of composition is sent to receiving end.
5. wireless sensor array data compression method according to claim 1, which is characterized in that the method is also wrapped
It includes:
In receiving end, the data packet being made of coding result and the optimum control vector is received；
According to the optimum control vector reconstruction spline curve in the data packet received, the original sensor array is obtained
The match value of data；
Hafman decoding is carried out to the coding result in the data packet received；
The match value of the original sensor array data is added with decoding result, obtains the original sensor array number
According to.
6. a kind of wireless sensor array data compression system characterized by comprising
First determining module, for using spline curve fitting original sensor array data, obtaining making the original in transmitting terminal
Spline interpolation expression formula when the match value error minimum of beginning sensor array data and the original sensor array data
Optimum control vector；
Second determining module, for obtaining the raw sensory according to the obtained optimum control vector reconstruction spline curve
The match value of device array data；
Third determining module, for calculating the fitting of the original sensor array data Yu the original sensor array data
Error and quantization between value；
Sending module is encoded, for carrying out Huffman encoding to the error after quantization, coding result and the optimum control are sweared
Amount is sent to receiving end.
7. wireless sensor array data compression system according to claim 6, which is characterized in that the optimum control arrow
Amount is expressed as:
Wherein,Indicate optimum control vector, A+Indicate that the generalized inverse matrix of A, A indicate the interpolation coefficient matrix of spline curve, Y
Indicate the original sensor array data.
8. wireless sensor array data compression system according to claim 6, which is characterized in that described second determines mould
Block includes:
Quantifying unit, for quantifying to the obtained optimum control vector；
Reconfiguration unit, for according to the optimum control vector reconstruction spline curve after quantization；
Determination unit obtains the match value of the original sensor array data for the spline curve according to reconstruct；
Wherein, the match value of the original sensor array data indicates are as follows: Indicate original sensor array data
Match value, A indicate spline curve interpolation coefficient matrix,Indicate optimum control vector.
9. wireless sensor array data compression system according to claim 6, which is characterized in that the coding sends mould
Block includes:
Coding unit, for carrying out Huffman encoding to the error after quantization；
Component units, for coding result and the optimum control vector to be constituted data packet；
Transmission unit, for the data packet of composition to be sent to receiving end.
10. wireless sensor array data compression system according to claim 6, which is characterized in that the system is also wrapped
It includes:
Receiving module, for receiving the data packet being made of coding result and the optimum control vector in receiving end；
4th determining module, for obtaining according to the optimum control vector reconstruction spline curve in the data packet received
The match value of the original sensor array data；
Decoder module, for carrying out Hafman decoding to the coding result in the data packet received；
5th determining module obtains described for the match value of the original sensor array data to be added with decoding result
Original sensor array data.
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