CN107064965A - A kind of GPS synchronous method - Google Patents
A kind of GPS synchronous method Download PDFInfo
- Publication number
- CN107064965A CN107064965A CN201710304869.9A CN201710304869A CN107064965A CN 107064965 A CN107064965 A CN 107064965A CN 201710304869 A CN201710304869 A CN 201710304869A CN 107064965 A CN107064965 A CN 107064965A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- mfrac
- munderover
- mtd
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04J—MULTIPLEX COMMUNICATION
- H04J3/00—Time-division multiplex systems
- H04J3/02—Details
- H04J3/06—Synchronising arrangements
- H04J3/0635—Clock or time synchronisation in a network
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Signal Processing (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The invention belongs to wireless communication technology field, it is related to a kind of GPS synchronous method.Main method of the present invention is：Signal and local synchronization signal is received first first to carry out the aliasing of time domain before FFT is carried out to reach reduction subsequent operation amount；Then the signal of aliasing is being subjected to FFT to frequency domain according to traditional synchronizing process；Both carry out conjugate multiplication again, and then progress IFFT transforms to time domain and obtains correlated series；The relevant peaks now obtained using the time-frequency conversion characteristic of aliasing sequence are the superpositions (containing actual synchronous peak) of some reference points in the correlated series of non-aliasing；Finally obtain the position of these points and carry out sub synchronous process and obtain final synchronous peak.The present invention improves traditional GPS synchronous method using the thought of sequence aliasing, and the present invention can obtain preferable synchronous effect, and substantially reduce the complexity of whole process.
Description
Technical field
The invention belongs to wireless communication technology field, it is related to signal in sparse Fourier transform (Sparse FFT, SFFT)
The decision threshold threshold value setting technology of the first synchronizing process of superimposing technique, more particularly to GPS positioning system.
Background technology
Traditional GPS synchronizing processes are widely used in real work, the improvement and innovation that can be made in this respect
Than relatively limited, the development of mobile network of today is very fast, and the GPS location of mobile terminal is also very frequent.It is mobile
The battery technology at end is a present development bottleneck, how to optimize power consumption under limited battery capacity and studies now
One focus.Reduce synchronous points after the superposition of rapid GPS synchronous operation synchronizing signal to reduce the scheme optimization of amount of calculation
Consumption when synchronous.
Traditional GPS synchronizing processes are typically to circulate correlated process in the local synchronizing sequence progress to reception to obtain related sequence
Row.Directly carry out circulation associative operation amount larger.Therefore FFT is generally carried out using receiving sequence and local sequence and operates again both
IFFT is carried out after conjugate multiplication to obtain correlated series quickly to obtain synchronous peak.
Rapid GPS synchronous method based on anti-aliasing operation, first carries out Time-domain aliasing operation before FFT operations are carried out, utilizes
Aliasing sequence transformation is the characteristic of the sampling of the frequency domain sequence of non-aliasing sequence to the sequence obtained after frequency domain.Reduce
Total points of FFT and IFFT changes are so as to reduce amount of calculation.
The content of the invention
The present invention proposes a kind of decision method at the synchronous peak after being superimposed in fast ripe GPS synchronization systems, can realize to GPS
Judging preliminary synchronisation position in synchronization system.
The present invention basic ideas be：Using the property of sparse Fourier transform, GPS synchronizing sequences are synchronizing operation
Preceding to be first overlapped, so as to reduce the synchronous points in synchronizing process, similarly local code is also so operated.Whole process
It is linear, then synchronize the superposition that the synchronizing sequence obtained after process is former synchronizing sequence.Initial synchronisation peak is found, then
The synchronous peak of former sequence is quickly found out from this point, can rapidly be synchronized.
Technical solution of the present invention is as follows：
The first synchronous method of a kind of GPS, as shown in figure 1, comprising the following steps：
Step 1：If reception synchronizing sequence is X=[X1,…,Xi,…,XN], line aliasing is entered to signal X, obtained after aliasing
Signal isWherein aliasing process is：
Step 2：To the signal X after aliasingBFFT is carried out to frequency domain：
The FFT after line aliasing is also similarly entered to frequency domain to local sequence R：
Step 3：By the reception frequency domain sequence F (X) of acquisitioni,BTake conjugation after with local frequency domain sequence F (R)i,BIt is conjugated
It is multiplied and obtains sequence Ci,B：
Step 4：By obtained sequence Ci,BIFFT is carried out, obtaining the correlated series after aliasing is
Signal X is in awgn channel, and the reception data of receiving end can be expressed as two paths of signals after treatment
Wherein nIAnd nQExpression variance is σ2Additive white Gaussian noise, P is signal power, and c (n) is the m sequences that permanent mould is 1
Row, m-sequence has good autocorrelation performance
The correlated series obtained after the relevant treatment of aliasing is expressed as
Here p=N/B, the average and variance of thus obtained signal
Step 5：Assuming that H1 is captures synchronous point, H0 is to capture asynchronous point.Have to H1 probability density function
Wherein I0 is 0 rank modified Bessel function, is had to H0
When relevant peaks appear in position for τ, i.e., it is more than remaining B-1 all value in the value of the correlation of τ positions,
Corresponding new probability formula is
The relevant peaks of the correlated series after aliasing are obtained using threshold judgement：
Wherein, signal to noise ratioVn is normalization thresholding, and Vn and actual thresholding Vt relation are：
Step 6：Obtain the p points of aliasing using aliasing correlation peak dot in step 5, to this p sub- correlated process of point progress from
And find actual synchronization point.Sub- correlated process will sequence that locally B points are obtained before sequence truncation and obtain receiving sequence P
The B point sequences of point position interception do correlation respectively.The synchronous process of this step neutron is synchronous with tradition GPS, difference is
Simply intercept these sequences progress associative operations for putting follow-up sub-fraction and obtain actual synchronization position.
The total technical scheme of the present invention, receives signal and local synchronization signal when first being carried out before carrying out FFT first
The aliasing in domain reduces the purpose of subsequent operation amount so as to reach；Then the signal of aliasing is carried out according to traditional synchronizing process
FFT is to frequency domain；Both carry out conjugate multiplication again, and then progress IFFT transforms to time domain and obtains correlated series；Utilize aliasing
The relevant peaks that the time-frequency conversion characteristic of sequence is now obtained are that the superposition of some reference points in the correlated series of non-aliasing (is included
Actual synchronous peak)；Finally obtain the position of these points and carry out sub synchronous process and obtain final synchronous peak.
Main method of the present invention is that the first synchronization to new Fast synchronization obtains just synchronous peak and quickly sentenced
Certainly, the grasp that can be shifted to an earlier date according to theory to the accurate judgement at synchronous peak.
Beneficial effects of the present invention are that the present invention improves traditional GPS synchronous method using the thought of sequence aliasing, makes
The complexity of whole process is substantially reduced.
Brief description of the drawings
Fig. 1 is the synchronous overall flow schematic diagram of rapid GPS；
Fig. 2 is that the actual synchronization detection probability curve comparison synchronous with theoretical formula of the synchronous just synchronizing process of rapid GPS shows
It is intended to.
Embodiment
Technical scheme is described in detail in the content of the invention, it is necessary to which supplement is, such as Fig. 2 institutes
Show, the validity of technical solution of the present invention is proved by Computer Simulation, and simulation result shows, in the aliasing of different points
Afterwards, the detection probability that correct synchronous peak is obtained after actual synchronization contrasts the simulation curve of theoretical formula, and both are sufficiently close to,
It is very high with degree.The correctness for being arranged such decision threshold is also demonstrated, to instructing Practical Project that there is foundation and the section of theory
The property learned.
Claims (1)
1. a kind of GPS synchronous method, it is characterised in that reduce synchronization complexity using aliasing process and corresponding decision threshold,
Comprise the following steps：
Step 1：If reception synchronizing sequence is X=[X1,…,Xi,…,XN], line aliasing is entered to signal X, the signal after aliasing is obtained
ForWherein aliasing process is：
<mrow>
<msub>
<mi>X</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>B</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>X</mi>
<mrow>
<mi>i</mi>
<mo>+</mo>
<mi>j</mi>
<mfrac>
<mi>N</mi>
<mi>B</mi>
</mfrac>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
<mn>1</mn>
<mo>,</mo>
<mo>...</mo>
<mo>,</mo>
<mfrac>
<mi>N</mi>
<mi>B</mi>
</mfrac>
<mo>-</mo>
<mn>1</mn>
</mrow>
Step 2：To the signal X after aliasingBFFT is carried out to frequency domain：
<mrow>
<mi>F</mi>
<msub>
<mrow>
<mo>(</mo>
<mi>X</mi>
<mo>)</mo>
</mrow>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>B</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>X</mi>
<mi>k</mi>
</msub>
<msup>
<mi>e</mi>
<mrow>
<mo>-</mo>
<mfrac>
<mrow>
<mi>j</mi>
<mn>2</mn>
<mi>&pi;</mi>
<mi>k</mi>
<mi>i</mi>
</mrow>
<mi>B</mi>
</mfrac>
</mrow>
</msup>
</mrow>
The FFT after line aliasing is also similarly entered to frequency domain to local sequence R：
<mrow>
<mi>F</mi>
<msub>
<mrow>
<mo>(</mo>
<mi>R</mi>
<mo>)</mo>
</mrow>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>B</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>R</mi>
<mi>k</mi>
</msub>
<msup>
<mi>e</mi>
<mrow>
<mo>-</mo>
<mfrac>
<mrow>
<mi>j</mi>
<mn>2</mn>
<mi>&pi;</mi>
<mi>k</mi>
<mi>i</mi>
</mrow>
<mi>B</mi>
</mfrac>
</mrow>
</msup>
</mrow>
Step 3：By the reception frequency domain sequence F (X) of acquisitioni,BTake conjugation after with local frequency domain sequence F (R)i,BCarry out conjugate multiplication
Obtain sequence Ci,B：
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<mo>=</mo>
<mi>F</mi>
<msub>
<mrow>
<mo>(</mo>
<mi>R</mi>
<mo>)</mo>
</mrow>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<mo>&CircleTimes;</mo>
<mi>F</mi>
<msubsup>
<mrow>
<mo>(</mo>
<mi>X</mi>
<mo>)</mo>
</mrow>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
<mo>*</mo>
</msubsup>
</mrow>
Step 4：By obtained sequence Ci,BIFFT is carried out, obtaining the correlated series after aliasing is：
<mrow>
<msub>
<mi>c</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<mo>=</mo>
<mi>I</mi>
<mi>F</mi>
<mi>F</mi>
<mi>T</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mi>B</mi>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>B</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>X</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>B</mi>
</mrow>
</msub>
<msup>
<mi>e</mi>
<mrow>
<mo>-</mo>
<mfrac>
<mrow>
<mi>j</mi>
<mn>2</mn>
<mi>&pi;</mi>
<mi>k</mi>
<mi>i</mi>
</mrow>
<mi>B</mi>
</mfrac>
</mrow>
</msup>
</mrow>
Synchronization sequence signals X is received in awgn channel, the reception data of receiving terminal can be expressed as two-way letter after treatment
Number：
<mrow>
<msub>
<mi>r</mi>
<mi>I</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<msqrt>
<mrow>
<mn>2</mn>
<mi>P</mi>
</mrow>
</msqrt>
<mn>2</mn>
</mfrac>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mi>c</mi>
<mi>o</mi>
<mi>s</mi>
<mi>&theta;</mi>
<mo>+</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<msub>
<mi>n</mi>
<mi>I</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mi>r</mi>
<mi>Q</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<msqrt>
<mrow>
<mn>2</mn>
<mi>P</mi>
</mrow>
</msqrt>
<mn>2</mn>
</mfrac>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mi>s</mi>
<mi>i</mi>
<mi>n</mi>
<mi>&theta;</mi>
<mo>+</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<msub>
<mi>n</mi>
<mi>Q</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
</mrow>
Wherein nIAnd nQExpression variance is σ2Additive white Gaussian noise, P is signal power, and c (n) is the m-sequence that permanent mould is 1, m
Sequence has good autocorrelation performance：
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mi>N</mi>
<mo>,</mo>
<mo>(</mo>
<mi>m</mi>
<mo>=</mo>
<mn>0</mn>
<mo>)</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
<mo>,</mo>
<mo>(</mo>
<mi>m</mi>
<mo>&NotEqual;</mo>
<mn>0</mn>
<mo>)</mo>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
The correlated series obtained after the relevant treatment of aliasing is expressed as：
<mrow>
<msub>
<mi>R</mi>
<mi>I</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>p</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>R</mi>
<mi>I</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>B</mi>
<mi>k</mi>
<mo>+</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<msqrt>
<mrow>
<mn>2</mn>
<mi>P</mi>
</mrow>
</msqrt>
<mn>2</mn>
</mfrac>
<mi>c</mi>
<mi>o</mi>
<mi>s</mi>
<mi>&theta;</mi>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>p</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>-</mo>
<mi>B</mi>
<mi>k</mi>
<mo>-</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>p</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>-</mo>
<mi>B</mi>
<mi>k</mi>
<mo>-</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>n</mi>
<mi>I</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mi>R</mi>
<mi>Q</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>p</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>R</mi>
<mi>Q</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>B</mi>
<mi>k</mi>
<mo>+</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<msqrt>
<mrow>
<mn>2</mn>
<mi>P</mi>
</mrow>
</msqrt>
<mn>2</mn>
</mfrac>
<mi>sin</mi>
<mi>&theta;</mi>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>p</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>-</mo>
<mi>B</mi>
<mi>k</mi>
<mo>-</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>p</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>c</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>-</mo>
<mi>B</mi>
<mi>k</mi>
<mo>-</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>n</mi>
<mi>Q</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
</mrow>
Here p=N/B, the average and variance of thus obtained aliasing signal
<mrow>
<mi>E</mi>
<mo>{</mo>
<msub>
<mi>R</mi>
<mi>I</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mo>}</mo>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mfrac>
<msqrt>
<mrow>
<mn>2</mn>
<mi>P</mi>
</mrow>
</msqrt>
<mn>2</mn>
</mfrac>
<mi>N</mi>
<mi>c</mi>
<mi>o</mi>
<mi>s</mi>
<mi>&theta;</mi>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>=</mo>
<mn>0</mn>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mn>0</mn>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>o</mi>
<mi>t</mi>
<mi>h</mi>
<mi>e</mi>
<mi>r</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
<mrow>
<mi>E</mi>
<mo>{</mo>
<msub>
<mi>R</mi>
<mi>Q</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mo>}</mo>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mfrac>
<msqrt>
<mrow>
<mn>2</mn>
<mi>P</mi>
</mrow>
</msqrt>
<mn>2</mn>
</mfrac>
<mi>N</mi>
<mi>sin</mi>
<mi>&theta;</mi>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>=</mo>
<mn>0</mn>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mn>0</mn>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>o</mi>
<mi>t</mi>
<mi>h</mi>
<mi>e</mi>
<mi>r</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
<mrow>
<msup>
<mi>&sigma;</mi>
<mn>2</mn>
</msup>
<mo>=</mo>
<mi>D</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>R</mi>
<mi>I</mi>
</msub>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>D</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>R</mi>
<mi>Q</mi>
</msub>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<msubsup>
<mi>pN&sigma;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
</mrow>
<mn>4</mn>
</mfrac>
</mrow>
Step 5：Assuming that H1 is captures synchronous point, H0 is to H1 probability density function to capture asynchronous point：
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>m</mi>
</msub>
<mo>|</mo>
<msub>
<mi>H</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<mn>4</mn>
<msub>
<mi>z</mi>
<mi>m</mi>
</msub>
</mrow>
<mrow>
<msubsup>
<mi>pN&sigma;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mfrac>
<mrow>
<mn>2</mn>
<msup>
<msub>
<mi>z</mi>
<mi>m</mi>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<mi>PN</mi>
<mn>2</mn>
</msup>
</mrow>
<mrow>
<msubsup>
<mi>pN&sigma;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
<msub>
<mi>I</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<mn>2</mn>
<msqrt>
<mrow>
<mn>2</mn>
<mi>P</mi>
</mrow>
</msqrt>
<msub>
<mi>Nz</mi>
<mi>m</mi>
</msub>
</mrow>
<mrow>
<msubsup>
<mi>pN&sigma;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
</mrow>
Wherein I0 is 0 rank modified Bessel function, is had to H0：
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>m</mi>
</msub>
<mo>|</mo>
<msub>
<mi>H</mi>
<mn>0</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<mn>4</mn>
<msub>
<mi>z</mi>
<mi>m</mi>
</msub>
</mrow>
<mrow>
<msubsup>
<mi>pN&sigma;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mfrac>
<mrow>
<mn>2</mn>
<msubsup>
<mi>z</mi>
<mi>m</mi>
<mn>2</mn>
</msubsup>
</mrow>
<mrow>
<msubsup>
<mi>pN&sigma;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
</mrow>
When relevant peaks appear in position for τ, i.e., it is more than remaining B-1 all values, correspondence in the value of the correlation of τ positions
New probability formula be：
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>&tau;</mi>
<mi>i</mi>
</msub>
<mo>=</mo>
<mi>&tau;</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Integral;</mo>
<msub>
<mi>v</mi>
<mi>t</mi>
</msub>
<mi>&infin;</mi>
</munderover>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>|</mo>
<msub>
<mi>H</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<msup>
<mrow>
<mo>(</mo>
<munderover>
<mo>&Integral;</mo>
<mn>0</mn>
<msub>
<mi>v</mi>
<mi>t</mi>
</msub>
</munderover>
<mi>f</mi>
<mo>(</mo>
<mrow>
<mi>z</mi>
<mo>|</mo>
<msub>
<mi>H</mi>
<mn>0</mn>
</msub>
</mrow>
<mo>)</mo>
<mi>d</mi>
<mi>z</mi>
<mo>)</mo>
</mrow>
<mrow>
<mi>B</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mi>d</mi>
<mi>x</mi>
</mrow>
The relevant peaks of the correlated series after aliasing are obtained using threshold judgement：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>&tau;</mi>
<mi>i</mi>
</msub>
<mo>=</mo>
<mi>&tau;</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<munderover>
<mo>&Integral;</mo>
<msub>
<mi>v</mi>
<mi>n</mi>
</msub>
<mi>&infin;</mi>
</munderover>
<mi>t</mi>
<mi> </mi>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<mo>-</mo>
<mrow>
<mo>(</mo>
<msup>
<mi>t</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<mn>2</mn>
<mi>B</mi>
<mi>s</mi>
<mi>n</mi>
<mi>r</mi>
<mo>)</mo>
</mrow>
</mrow>
<mn>2</mn>
</mfrac>
<mo>)</mo>
</mrow>
<msub>
<mi>I</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<msqrt>
<mrow>
<mn>2</mn>
<mi>B</mi>
<mi>s</mi>
<mi>n</mi>
<mi>r</mi>
<mi>t</mi>
</mrow>
</msqrt>
<mo>)</mo>
</mrow>
<msup>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>-</mo>
<mi>exp</mi>
<mo>(</mo>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<mo>-</mo>
<msup>
<mi>t</mi>
<mn>2</mn>
</msup>
</mrow>
<mn>2</mn>
</mfrac>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mrow>
<mi>B</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mi>d</mi>
<mi>t</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
Wherein, signal to noise ratioVn is normalization thresholding, and Vn and actual thresholding Vt relation are：
<mrow>
<msub>
<mi>v</mi>
<mi>n</mi>
</msub>
<mo>=</mo>
<mfrac>
<msub>
<mi>v</mi>
<mi>t</mi>
</msub>
<msqrt>
<mfrac>
<mrow>
<msubsup>
<mi>pN&sigma;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
</mrow>
<mn>4</mn>
</mfrac>
</msqrt>
</mfrac>
</mrow>
Step 6：The p points of aliasing are obtained using aliasing correlation peak dot in step 5, this p point is carried out sub- correlated process to look for
To actual synchronization point, sub- correlated process will sequence that locally B points are obtained before sequence truncation and the P point that obtains receiving sequence
The B point sequences for putting interception do correlation respectively.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710304869.9A CN107064965B (en) | 2017-05-03 | 2017-05-03 | A kind of GPS synchronous method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710304869.9A CN107064965B (en) | 2017-05-03 | 2017-05-03 | A kind of GPS synchronous method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107064965A true CN107064965A (en) | 2017-08-18 |
| CN107064965B CN107064965B (en) | 2019-04-12 |
Family
ID=59597690
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710304869.9A Expired - Fee Related CN107064965B (en) | 2017-05-03 | 2017-05-03 | A kind of GPS synchronous method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107064965B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101064700A (en) * | 2006-04-26 | 2007-10-31 | 电子科技大学 | Method for synchronization of multi-input multi-output OFDM system |
| CN102435999A (en) * | 2011-10-26 | 2012-05-02 | 浙江理工大学 | Baseband module of GPS (global positioning system) receiver and GPS signal acquiring and tracing method |
| CN102664656A (en) * | 2012-04-18 | 2012-09-12 | 北京理工大学 | Direct sequence spread spectrum signal compressed domain united synchronization and demodulation method based on structured sparsity |
| CN106338751A (en) * | 2015-12-25 | 2017-01-18 | 深圳艾科创新微电子有限公司 | Satellite signal bit synchronization method and device, and navigation receiver |
-
2017
- 2017-05-03 CN CN201710304869.9A patent/CN107064965B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101064700A (en) * | 2006-04-26 | 2007-10-31 | 电子科技大学 | Method for synchronization of multi-input multi-output OFDM system |
| CN102435999A (en) * | 2011-10-26 | 2012-05-02 | 浙江理工大学 | Baseband module of GPS (global positioning system) receiver and GPS signal acquiring and tracing method |
| CN102664656A (en) * | 2012-04-18 | 2012-09-12 | 北京理工大学 | Direct sequence spread spectrum signal compressed domain united synchronization and demodulation method based on structured sparsity |
| CN106338751A (en) * | 2015-12-25 | 2017-01-18 | 深圳艾科创新微电子有限公司 | Satellite signal bit synchronization method and device, and navigation receiver |
Non-Patent Citations (1)
| Title |
|---|
| 刘清华: "基于稀疏快速傅里叶变换的信号压缩处理", 《微型机与应用》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107064965B (en) | 2019-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103746722B (en) | Method for estimating jump cycle and take-off time of frequency hopping signal | |
| CN106534031B (en) | A kind of LTE downlink frame synchronization method of low complex degree | |
| CN108494518B (en) | A kind of LTE system small region search method | |
| CN104093168B (en) | A kind of LTE homogeneous-frequency adjacent-domains detection method and device | |
| CN111132272A (en) | Cell search timing synchronization method for 5G NR system | |
| CN103618686B (en) | Method for accurately estimating underwater sound OFDM Doppler factor | |
| CN105607096A (en) | Dual-satellite time difference and frequency difference positioning method and positioning device | |
| CN103905355A (en) | Virtual time reversal underwater sound OFDM channel equalization method | |
| CN102638335B (en) | Cross-correlation and autocorrelation cascade based frame synchronizing method | |
| CN102026231A (en) | Method for detecting random access of wireless communication system | |
| CN102238125B (en) | Integral multiple frequency offset estimation method of OFDM (orthogonal frequency division multiplexing) system with residual time bias | |
| CN102984719B (en) | Master sync signal detection method, device and terminal based on pretreatment | |
| CN107064965A (en) | A kind of GPS synchronous method | |
| CN102868420B (en) | LTE (long-term evolution) synchronous method | |
| CN103701489A (en) | Correlated peak position information-based time synchronization method for underwater acoustic spread spectrum communication | |
| CN102065035B (en) | Channel estimation method of multi-band orthogonal frequency-division multiplexing ultra-wideband system | |
| CN109769294A (en) | A kind of synchronous method based on FDD-LTE system | |
| CN103166899A (en) | Symbol blind synchronization method for zero prefix-orthogonal frequency division multiplexing system | |
| CN100521565C (en) | A cell searching method and device for TD-SCDMA system | |
| CN104123267B (en) | High-precision fine synchronization device and method | |
| CN102469046A (en) | Estimation method of timing advance and system thereof | |
| CN102932312B (en) | Multipath adjusting method for OFDM power line carrier communication system | |
| CN107426131A (en) | A kind of low relevant search peak timing estimation method of anti-frequency deviation based on cyclic prefix | |
| CN102123128B (en) | Blind timing synchronization method based on circular structure | |
| CN101808071B (en) | Synchronizing method of OFDM (Orthogonal Frequency Division Multiplexing) system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190412 |