CN103543456A - Large frequency offset GNSS signal capture method based on segmentation relative combination FFT operation - Google Patents

Abstract

The invention discloses a large frequency offset GNSS signal capture method based on a segmentation relative combination FFT operation. According to the method, by means of the segmentation relative combination FFT operation, parallel searching of carrier frequencies can be completed when serial searching of a code phase is carried out, capture time of a large frequency offset GNSS signal is greatly shortened, and loss of the signal to noise ratio is little. In detail, according to the method, firstly, a received signal is divided into a plurality of subsections, the subsections and a local pseudo code undergo relative operations to obtain a plurality of relative values, then zero fill is carried out on a relative value sequence, the FFT operation is carried out, ultimately the maximum value of the moduluses of the operation result is judged, if the value is higher than a judgment threshold, the code phase is the code phase obtained through capture, the frequency point corresponding to the value is the captured carrier frequency, if the value is smaller than the judgment threshold, the phase of a local code is adjusted, and the process continues to be carried out until time frequency two-dimensional searching of the large frequency offset GNSS signal is finished.

Description

A kind of based on the relevant large frequency deviation GNSS signal acquisition methods in conjunction with FFT computing of segmentation

Technical field

The invention belongs to GPS (Global Position System) receiver spread-spectrum signal process field, a kind of based on the relevant carrier frequency capturing method in conjunction with FFT computing of segmentation specifically.

Background technology

GLONASS (Global Navigation Satellite System) (Global Navigation Satellite System, GNSS) can be user provides successional Position, Velocity and Time information, can meet navigation, locates, tests the speed, the many services requirement such as time service and rescue.The whole world mainly contains four large satellite navigational system at present: the Galileo system in the gps system of the U.S., Muscovite GLONASS system, Europe and the dipper system of China.These systems all in the mode of CDMA or frequency division multiple access to the round-the-clock broadcasting satellite signal of global user.

As shown in Figure 1, it is the basis of various spread-spectrum signal code Acquisition Scheme to the Acquisition Scheme basic structure of GNSS spread-spectrum signal code.The basic procedure of signal capture is: base-band spread-spectrum signal C (t) obtains detection limit with S (t) through, integration relevant to local code, a square summation, detection limit is adjudicated, if detection limit surpasses detection threshold, think and catch, otherwise adjust local spreading code phase place, carry out the detection of next phase place.

When receiver moves at a relatively high speed, can there is larger Doppler's carrier frequency shift in above-mentioned baseband signal, now in signal capture process, needs the reference carrier frequency of search larger.When adopting traditional carrier frequency serial search strategy, the signal capture time is longer.Therefore, be necessary to find a kind of Doppler frequency offset estimation method fast, to realize the accurate estimation to large frequency offset signal carrier frequency.

Summary of the invention

The object of the invention is to overcome the weak point in above-mentioned background, provide a kind of based on the relevant large frequency deviation GNSS signal acquisition methods in conjunction with FFT computing of segmentation.

The method is correlated with in conjunction with FFT computing by segmentation, can in code phase serial search, complete the parallel search of carrier frequency, greatly shortened the capture time of large frequency deviation GNSS signal, and snr loss is less, and its theory diagram as shown in Figure 2.The present invention mainly comprises following step:

The first step: digital signal samples.

Receive signal after Digital Down Convert, obtain baseband signal (containing Doppler frequency deviation) and be:

$r\left(k\right)=D\left(k\right)\mathrm{PN}\left(k\right)e^{j(2\mathrm{\π}{f}_{d}k{T}_s-\mathrm{\θ})}$

Wherein D (k) is binary modulated information, and PN (k) is spread spectrum code sequence, f _dfor Doppler frequency deviation, T _sfor the spread-spectrum code chip cycle, θ is carrier phase.

Second step: the reception signal and the local pseudo-code that are M chip by length are divided into respectively R subsegment, every segment length P=M/R, then the accumulating operation of corresponding subsegment being correlated with respectively, in the situation that temporarily not considering binary modulated informational influence, obtains correlation:

$\begin{array}{c}C\left(i\right)=\underset{k=(i-1)*P+1}{\overset{i*P}{\mathrm{\Σ}}}\mathrm{PN}\left(k\right)\mathrm{PN}(k+\mathrm{\Δ})e^{j(2\mathrm{\π}{f}_{d}k{T}_s-\mathrm{\θ})}\\ =\underset{k=(i-1)*P+1}{\overset{i*P}{\mathrm{\Σ}}}R\left(\mathrm{\Δ}\right)e^{j(2\mathrm{\π}{f}_{d}k{T}_s-\mathrm{\θ})}\\ =R\left(\mathrm{\Δ}\right)\·e^{j[(2\mathrm{\π}{f}_d(i-1)*P+1)T_s-\mathrm{\θ}]}\frac{1-e^{j\left(2\mathrm{\π}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\π}{f}_d{T}_s\right)}}\end{array}$

I=1 wherein, 2,3...R, the autocorrelation function that R (Δ) is spreading code, Δ is for receiving the phase differential of signal and local spreading code.

The 3rd step: will carry out FFT computing after sequence of correlation values zero padding.

By carrying out the FFT computing that S is ordered after R relevant value complement S-R individual 0, obtaining S FFT output valve, be:

$\begin{array}{c}{Z}_c\left(m\right)+j*Z_s\left(m\right)=\underset{i=1}{\overset{S}{\mathrm{\&Sigma;}}}C\left(i\right)e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">j</figure-callout>}\frac{2\mathrm{\&pi;}}{S}\mathrm{im}}=\underset{i=1}{\overset{R}{\mathrm{\&Sigma;}}}C\left(i\right)e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">j</figure-callout>}\frac{2\mathrm{\&pi;}}{S}\mathrm{im}}\\ =\underset{i=1}{\overset{R}{\mathrm{\&Sigma;}}}R\left(\mathrm{\&Delta;}\right)\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;e^{j\left\{2\mathrm{\&pi;}{f}_d\right[(i-1)P+1]T_s-\frac{2\mathrm{\&pi;}}{S}\mathrm{im}-\mathrm{\&theta;}\}}\\ =R\left(\mathrm{\&Delta;}\right)\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;e^{j[2\mathrm{\&pi;}{f}_d(1-p)T_s-\mathrm{\&theta;}]}\&CenterDot;\frac{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}\\ =R\left(\mathrm{\&Delta;}\right)\&CenterDot;e^{j[2\mathrm{\&pi;}{f}_d(1-p)T_s-\mathrm{\&theta;}]}\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;\frac{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}\end{array}$

The 4th step: to FFT computing Output rusults delivery.

To FFT output valve delivery, obtain Acquisition Detection amount:

$\begin{array}{c}Z\left(m\right)=|{Z^2}_c\left(m\right)+{Z^2}_s\left(m\right)|={|R\left(\mathrm{\&Delta;}\right)\&CenterDot;e^{j[2\mathrm{\&pi;}{f}_d(1-p)T_s-\mathrm{\&theta;}]}\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;\frac{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}|}^2\\ ={|R\left(\mathrm{\&Delta;}\right)\&CenterDot;\frac{\sin \left(\mathrm{\&pi;}{f}_{d}P{T}_s\right)}{\sin \left(\mathrm{\&pi;}{f}_d{T}_s\right)}\&CenterDot;\frac{\sin \left[\mathrm{\&pi;R}(f_{d}P{T}_s-\frac{m}{S})\right]}{\sin \left[\mathrm{\&pi;}(f_{d}P{T}_s-\frac{m}{S})\right]}|}^2\\ =R{\left(\mathrm{\&Delta;}\right)}^2\&CenterDot;{\left|\frac{\sin \left(\frac{M}{R}\mathrm{\&pi;}{f}_d{T}_s\right)}{\sin \left(\mathrm{\&pi;}{f}_d{T}_s\right)}\right|}^2\&CenterDot;{\left|\frac{\sin \left[\mathrm{\&pi;R}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}{\sin \left[\mathrm{\&pi;}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}\right|}^2\end{array}$

The 5th step: maximum norm value is adjudicated.

When reception signal spread-spectrum code phase is not synchronizeed with local spreading code phase place, R (Δ) ≈ 0, maximum norm value is no more than threshold value, at this moment needs to adjust local code phase place, continues execution step two to step 5.

When receiving signal spread-spectrum code phase and local spreading code phase place basic synchronization, R (Δ) ≈ 1, Acquisition Detection amount is as follows:

$Z\left(m\right)={\left|\frac{\sin \left(\frac{M}{R}\mathrm{\&pi;}{f}_d{T}_s\right)}{\sin \left(\mathrm{\&pi;}{f}_d{T}_s\right)}\right|}^2\&CenterDot;{\left|\frac{\sin \left[\mathrm{\&pi;R}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}{\sin \left[\mathrm{\&pi;}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}\right|}^2$

Wherein, first is the snr loss that in integration section, frequency deviation causes, only relevant with input Doppler frequency difference, irrelevant with m value; Second size changes with m value, when

time, corresponding

make this value reach maximum (wherein [] represents to round operation), now Acquisition Detection amount Z (m) ≈ M ², the Doppler frequency deviation estimated value that acquisition procedure obtains

When

during for non-integer, can not exclusively cause certain snr loss because of phase compensation.Use this method to carry out in signal capture process, signal to noise ratio (S/N ratio) total losses with the variation of input Doppler frequency deviation value as shown in Figure 3.

Accompanying drawing explanation

Fig. 1 is code acquisition basic structure block diagram;

Fig. 2 is that segmentation of the present invention is relevant in conjunction with FFT computing signal capture theory diagram;

Fig. 3 is that segmentation of the present invention is correlated with in conjunction with snr loss in FFT computing signal capture process with the change curve of carrier doppler frequency deviation size;

Fig. 4 is that segmentation of the present invention is relevant in conjunction with FFT computing signal capture correlation distribution plan;

Embodiment

The present invention propose based on the relevant large frequency deviation GNSS signal acquisition methods in conjunction with FFT computing of segmentation, the gps signal of take is described as follows as example.

This method Frequency Estimation scope is

frequency Estimation precision is

nonlinear Transformation in Frequency Offset Estimation scope according to demand and estimated accuracy are determined the size of segment length M/R and the FFT S that counts.

The first step: digital signal samples.

Receive gps signal after Digital Down Convert, obtain baseband signal (containing Doppler frequency deviation) and be:

$r\left(k\right)=D\left(k\right)\mathrm{PN}\left(k\right)e^{j(2\mathrm{\&pi;}{f}_{d}k{T}_s-\mathrm{\&theta;})}$

Wherein D (k) is GPS text modulation intelligence; PN (k) is gps satellite spread spectrum code sequence; f _dfor Doppler frequency deviation, size is 40KHz; T _sfor the spread-spectrum code chip cycle, size is

θ is carrier phase.

Second step: the reception signal of length M=1023 chip and local pseudo-code are divided into respectively to R=93 subsegment, every segment length P=M/R=11, then the accumulating operation of corresponding subsegment being correlated with respectively, in the situation that temporarily not considering binary modulated informational influence, obtains correlation:

$\begin{array}{c}C\left(i\right)=\underset{k=(i-1)*P+1}{\overset{i*P}{\mathrm{\&Sigma;}}}\mathrm{PN}\left(k\right)\mathrm{PN}(k+\mathrm{\&Delta;})e^{j(2\mathrm{\&pi;}{f}_{d}k{T}_s-\mathrm{\&theta;})}\\ =\underset{k=(i-1)*P+1}{\overset{i*P}{\mathrm{\&Sigma;}}}R\left(\mathrm{\&Delta;}\right)e^{j(2\mathrm{\&pi;}{f}_{d}k{T}_s-\mathrm{\&theta;})}\\ =R\left(\mathrm{\&Delta;}\right)\&CenterDot;e^{j[(2\mathrm{\&pi;}{f}_d(i-1)*P+1)T_s-\mathrm{\&theta;}]}\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\end{array}$

I=1 wherein, 2,3..., the autocorrelation function that 93, R (Δ) is spreading code, Δ is for receiving the phase differential of signal and local spreading code.

The 3rd step: will carry out FFT computing after sequence of correlation values zero padding.

By carrying out the FFT computing that S=512 is ordered after R=93 relevant value complement S-R=512-93=419 individual 0, obtaining S=512 FFT output valve, be:

$\begin{array}{c}{Z}_c\left(m\right)+j*Z_s\left(m\right)=\underset{i=1}{\overset{S}{\mathrm{\&Sigma;}}}C\left(i\right)e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">j</figure-callout>}\frac{2\mathrm{\&pi;}}{S}\mathrm{im}}=\underset{i=1}{\overset{R}{\mathrm{\&Sigma;}}}C\left(i\right)e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">j</figure-callout>}\frac{2\mathrm{\&pi;}}{S}\mathrm{im}}\\ =\underset{i=1}{\overset{R}{\mathrm{\&Sigma;}}}R\left(\mathrm{\&Delta;}\right)\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;e^{j\left\{2\mathrm{\&pi;}{f}_d\right[(i-1)P+1]T_s-\frac{2\mathrm{\&pi;}}{S}\mathrm{im}-\mathrm{\&theta;}\}}\\ =R\left(\mathrm{\&Delta;}\right)\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;e^{j[2\mathrm{\&pi;}{f}_d(1-p)T_s-\mathrm{\&theta;}]}\&CenterDot;\frac{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}\\ =R\left(\mathrm{\&Delta;}\right)\&CenterDot;e^{j[2\mathrm{\&pi;}{f}_d(1-p)T_s-\mathrm{\&theta;}]}\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;\frac{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}\end{array}$

The 4th step: to FFT computing Output rusults delivery.

To FFT output valve delivery, obtain Acquisition Detection amount:

$\begin{array}{c}Z\left(m\right)=|{Z^2}_c\left(m\right)+{Z^2}_s\left(m\right)|={|R\left(\mathrm{\&Delta;}\right)\&CenterDot;e^{j[2\mathrm{\&pi;}{f}_d(1-p)T_s-\mathrm{\&theta;}]}\&CenterDot;\frac{1-e^{j\left(2\mathrm{\&pi;}{f}_{d}P{T}_s\right)}}{1-e^{j\left(2\mathrm{\&pi;}{f}_d{T}_s\right)}}\&CenterDot;\frac{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}{1-{\mathrm{<figure-callout\; id="2"\; label="e\; j"\; filenames="HSA0000096671450000021.png,HSA0000096671450000022.png"\; state="\{\{state\}\}">e</figure-callout>}}^j}|}^2\\ ={|R\left(\mathrm{\&Delta;}\right)\&CenterDot;\frac{\sin \left(\mathrm{\&pi;}{f}_{d}P{T}_s\right)}{\sin \left(\mathrm{\&pi;}{f}_d{T}_s\right)}\&CenterDot;\frac{\sin \left[\mathrm{\&pi;R}(f_{d}P{T}_s-\frac{m}{S})\right]}{\sin \left[\mathrm{\&pi;}(f_{d}P{T}_s-\frac{m}{S})\right]}|}^2\\ =R{\left(\mathrm{\&Delta;}\right)}^2\&CenterDot;{\left|\frac{\sin \left(\frac{M}{R}\mathrm{\&pi;}{f}_d{T}_s\right)}{\sin \left(\mathrm{\&pi;}{f}_d{T}_s\right)}\right|}^2\&CenterDot;{\left|\frac{\sin \left[\mathrm{\&pi;R}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}{\sin \left[\mathrm{\&pi;}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}\right|}^2\end{array}$

The 5th step: maximum norm value is adjudicated.

When reception signal spread-spectrum code phase is not synchronizeed with local spreading code phase place, R (Δ) ≈ 0, maximum norm value is no more than threshold value, at this moment needs to adjust local code phase place, continues execution step two to step 5.

When receiving signal spread-spectrum code phase and local spreading code phase place basic synchronization, R (Δ) ≈ 1, Acquisition Detection amount is as follows:

$\begin{array}{c}Z\left(m\right)={\left|\frac{\sin \left(\frac{M}{R}\mathrm{\&pi;}{f}_d{T}_s\right)}{\sin \left(\mathrm{\&pi;}{f}_d{T}_s\right)}\right|}^2\&CenterDot;{\left|\frac{\sin \left[\mathrm{\&pi;R}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}{\sin \left[\mathrm{\&pi;}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}\right|}^2\\ ={\left|\frac{\sin (\frac{1023}{93}\&times;\mathrm{\&pi;}\&times;(40\&times;{10}^3)\&times;(\frac{1}{1.023}\&times;{10}^{-6}))}{\sin (\mathrm{\&pi;}\&times;(40\&times;{10}^3)\&times;(\frac{1}{1.023}\&times;{10}^{-6}))}\right|}^2\&times;\\ {\left|\frac{\sin [\mathrm{\&pi;}\&times;93\&times;((40\&times;{10}^3)\&times;\frac{1023}{93}\&times;(\frac{1}{1.023}\&times;{10}^{-6})-\frac{m}{512})]}{\sin [\mathrm{\&pi;}\&times;((40\&times;{10}^3)\&times;\frac{1023}{93}\&times;(\frac{1}{1.023}\&times;{10}^{-6})-\frac{m}{512})]}\right|}^2\end{array}$

When $\mathrm{\&pi;}\&times;93\&times;((40\&times;{10}^3)\&times;\frac{1023}{93}\&times;(\frac{1}{1.023}\&times;{10}^{-6})-\frac{m}{512})=0$ Time, this gets maximal value, and now corresponding m value size is

doppler frequency deviation estimated value is $f_d=\frac{\mathrm{mR}}{{\mathrm{SMT}}_s}=39.961\mathrm{KHz},$ Estimated frequency error is 40Hz.

Claims (6)

1. based on the relevant large frequency deviation GNSS signal acquisition methods in conjunction with FFT computing of segmentation, its feature comprises following five steps:

Steps A: digital signal samples;

Step B: whole chip is divided into R subsegment, and by the corresponding subsegment accumulating operation of being correlated with respectively;

Step C: will carry out FFT computing after sequence of correlation values zero padding;

Step D: to FFT computing Output rusults delivery;

Step e: maximum norm value is adjudicated.

2. large frequency deviation GNSS signal acquisition methods according to claim 1, is characterized in that: the baseband signal of extracting in steps A is

wherein D (k) is binary modulated information, and PN (k) is spread spectrum code sequence, f _dfor Doppler frequency deviation, T _sfor the spread-spectrum code chip cycle, θ is carrier phase.

3. large frequency deviation GNSS signal acquisition methods according to claim 1, is characterized in that: the baseband signal that is M by chip lengths in step B is divided into R section, and every segment length is P, and has P=M/R.

4. large frequency deviation GNSS signal acquisition methods according to claim 1, is characterized in that: in step C, will after R relevant value complement S-R individual 0, carry out the FFT computing that S is ordered.

5. large frequency deviation GNSS signal acquisition methods according to claim 1, is characterized in that: Output rusults delivery in step D $Z\left(m\right)={\left|\frac{\sin \left(\frac{M}{R}\mathrm{\&pi;}{f}_d{T}_s\right)}{\sin \left(\mathrm{\&pi;}{f}_d{T}_s\right)}\right|}^2\&CenterDot;{\left|\frac{\sin \left[\mathrm{\&pi;R}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}{\sin \left[\mathrm{\&pi;}(f_d\frac{M}{R}{T}_s-\frac{m}{S})\right]}\right|}^2,$ In detection limit, first irrelevant with m value, and the second item size changes with m.

6. large frequency deviation GNSS signal acquisition methods according to claim 1, is characterized in that: in step e, compare Output rusults and the judging threshold of FFT, if be less than threshold value, re-execute step B.

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