CN101567730B - Signal estimation and detection method based on nonlinear transformation - Google Patents

Abstract

The invention relates to a signal estimation and detection method based on nonlinear transformation. The method gives two hypotheses: one hypothesis is that a wireless spectrum signal H0, namely y(t)=n(t) is nonexistent, and the other hypothesis is that a wireless spectrum signal H1, namely y(t)=x(t)+n(t) is existent. Detection whether a signal x(t) exists in a received signal y(t) comprises the following steps: 1) nonlinear transformation, namely performing the nonlinear transformation on the received broadband signal y(t) by a nonlinear transformer to obtain a nonlinear signal f(t); 2) characteristic extraction, namely extracting correlated characteristics of signals from the signal f(t) after the nonlinear transformation, and using the correlated characteristics as an apriori knowledgeto be provided to a matched filter; 3) matched filtering detection, namely performing match detection on the received signal y(t) by a matched filter according to the apriori knowledge obtained in the step 2), and using the matched result as a reason for a decision; and 4) decision, namely judging the detection result of the matched filter by a decision device according to a set decision threshold, and determining whether the signal x(t) exists. The method has the advantages of strong real-time, high accuracy of signal estimation and detection, simple system structure, low operation complexity and short detection time.

Description

Signal based on nonlinear transformation is estimated and detection method

Technical field

The present invention relates to the estimation and the detection technique of random signal, under low signal-to-noise ratio (SNR) environment, estimate and detection method based on the signal of nonlinear transformation more specifically to a kind of.

Background technology

Current, show growing spectrum requirement and the contradiction day between the limited frequency spectrum resources outstanding, seriously restricted the development of radio communication service.But from actual wireless frequency spectrum operation situation, distribute the wireless frequency spectrum of (mandate) on time and space, to exist the idle of certain degree, according to the measurement data report to wireless frequency spectrum, the frequency spectrum utilization rate of most of radio band is only about 10%.How effectively to solve the contradiction of the rare and frequency spectrum utilization rate of frequency spectrum resource between low and become the key technology in the radio communication.The UWB that gives cognitive radio (CR) function is acknowledged as the effective technology means of efficiently utilizing wireless frequency spectrum.

UWB is with its two-forty, high-performance, low-power consumption, advantage has huge development potentiality in high speed short-distance wireless communication, particularly streaming media service cheaply.Wireless environment is the prerequisite of cognitive ultra-wideband (CR-UWB) work with detecting on every side in correct perception.The method of cognition wireless signal sensing and detection can be divided into three major types at present: energy measuring, matched filter detect and cyclostationary characteristic detects.Energy measuring is to be that module is sought suitable frequency spectrum hole with the interference temperature, is to use the widest a kind of frequency spectrum detecting method at present.But the interference temperature thresholding of energy measuring is difficult to confirm, and when pickup electrode is weak, is difficult to distinguish signal, noise and interference, suitable as UWB the applied environment of low signal-to-noise ratio.The matched filter detection architecture is simple, can reach very high input accuracy rate, but needs to understand the priori of signal to be detected, thereby has limited the application of this detection method, also is not suitable for the use under the UWB environment.Can distinguish signal according to the difference of signal characteristic peak in the frequency spectrum three dimensions based on the steady feature detection of signal cycle, need not understand the priori of detection signal, under very low SNR situation, still have good detection performance.But need carry out high-order (second order and more than the second order) statistic to signal based on the cyclostationary characteristic detection; The statistical space of signal is complete again; Computational complexity is high, and detection time is long, is not suitable for as streaming media service in the exigent UWB applied environment of some network real-time property.

Summary of the invention

The objective of the invention is to overcome the deficiency of above-mentioned prior art, solve a difficult problem that lacks seized signal priori in the matched filter detection method, design a kind of signal sensing detection method of quick, the accurate and effective realization of ability under the low signal-to-noise ratio environment.

Above-mentioned purpose is achieved through following technical proposals:

The wireless frequency spectrum signal that surrounding environment is existed carries out two kinds of hypothesis: there is not wireless frequency spectrum signal H in the first ₀It two is to have wireless frequency spectrum signal H ₁

H ₀：y(t)＝n(t)

H ₁：y(t)＝x(t)+n(t)

N (t) representes additive Gaussian noise, the wireless frequency spectrum signal that x (t) expression has been authorized, and the signal that receives is y (t), 0≤t≤T.To whether existing signal x (t) to estimate among the signal y (t) and detecting, comprise the following steps:

1) nonlinear transformation is carried out nonlinear transformation with the broadband signal y that receives (t) through the non-linear converter, obtains nonlinear properties f (t);

2) correlated characteristic of signal is extracted in feature extraction the signal f (t) after nonlinear transformation, and offers matched filter as priori;

3) matched filtering detects, and matched filter is according to step 2) in the priori that draws said reception signal y (t) is carried out matching detection, matching result is as the foundation of judgement;

4) judgement, decision device are judged the matched filter testing result according to the decision threshold of setting judge whether there is signal x (t).

Further design is that the non-linear converter in the said step 1) does

f(t)＝ay ²(t)-by(t-τ ₁)y(t+τ ₂)-cy(t-τ ₃)

Wherein a, b and c are weight coefficient, τ ₁, τ ₂And τ ₃It is respectively time-delay correlation time.

Further design is said step 2) in obtaining of said priori be:

1) the signal f (t) after the nonlinear transformation is carried out time-frequency conversion through fast Fourier transformer and obtain time-frequency conversion signal F (f)

$F\left(f\right)={\∫}_0^{T}f\left(t\right)e^{-j2\mathrm{\πft}}\mathrm{dt};$

2), and obtain the pairing frequency f of maximum in view of the above to the F behind the time-frequency conversion (f) delivery (absolute value) ₀With three dB bandwidth B, as the priori spectrum signature of signal x (t), i.e. priori.

Further design is, the said matching detection in the said step 3) be according to said priori through matched filter to received signal y (t) carry out matched filtering, export filtering signal s (t)

$s\left(t\right)={\∫}_0^{T}y(t-\mathrm{\τ})h\left(\mathrm{\τ}\right)\mathrm{d\τ}$

Matched filter function h (t) is by priori f ₀Decision, i.e. h (t)=cos [2 π f ₀(T-t)]+sin [2 π f ₀(T-t)], wherein τ is a delay time.

Further design is that said step 4) decision threshold is set at η

η＝α|F(f)| ²/B

Wherein alpha will be set according to the false alarm rate and the false dismissed rate of system requirements.

Decision device detects said output filtering signal s (t) according to above-mentioned decision threshold η, if H ₀Set up, receive signal y (t)=n (t), wherein do not contain signal x (t), can use y (t) corresponding frequency band to communicate; If H ₁Set up, contain signal x (t) in y (t) corresponding frequency band, therefore cannot use the corresponding frequency range of y (t) to communicate.

The inventive method is applied to nonlinear transformation through nonlinear transformation seized signal to be made an estimate in the matched filter detection, and the priori of rapid extraction signal realizes quick, the accurately perception and the detection of signal.Be exactly that nonlinear transformation combines with matched filter specifically, nonlinear transformation rapid extraction signal characteristic, accurate perception of matched filter and detection signal have solved a difficult problem that lacks seized signal priori in the matched filter detection method.Thereby the beneficial effect below producing:

(1) through nonlinear transformation, realize the rapid extraction of signal priori, real-time;

(2) detect through matched filter, realize the accurate detection of signal;

(3) decision threshold has adaptation function, can fit the dynamic change of UWB channel, improves signal and estimates and the detection accuracy rate;

(4) system configuration is simple, computational complexity is low, detection time is short.Detecting the less demanding occasion of accuracy rate, the feature extraction result after the nonlinear transformation can directly be used for judgement.This moment, system configuration was simpler, and detection time is shorter.

Description of drawings

Fig. 1 is that the signal based on nonlinear transformation of the present invention is estimated and the method block diagram that detects.

Embodiment

Below in conjunction with accompanying drawing and specific embodiment the present invention is further specified.

Given two kinds of hypothesis, H ₀Only there is additive Gaussian noise n (t) in-surrounding environment; H ₁There are the wireless frequency spectrum signal x (t) and additive Gaussian noise n (t) that distribute (mandate) in-the surrounding environment, promptly

H ₀：y(t)＝n(t)

H ₁：y(t)＝x(t)+n(t)

If the signal that receives is y (t), 0≤t≤T.

Whether exist signal x (t) to estimate and detection among the existing signal y (t) to acceptance, implementation step block diagram as shown in Figure 1, specific as follows:

Y (t) carries out nonlinear transformation at first to the received signal.Adopt a kind of simple nonlinear to be transformed to

f(t)＝y ²(t)

In fact above-mentioned nonlinear transformation process is exactly a square of process, employing be exactly a squarer.

Also can carry out conversion, be like the typical nonlinear converter through other non-linear converter:

f(t)＝ay ²(t)-by(t-τ ₁)y(t+τ ₂)-cy(t-τ ₃)

Wherein a, b and c are weight coefficient, τ ₁, τ ₂And τ ₃It is respectively time-delay correlation time.

Letter f (t) after the nonlinear transformation is carried out time-frequency conversion

$F\left(f\right)={\∫}_0^{T}f\left(t\right)e^{-j2\mathrm{\πft}}\mathrm{dt}$

Above-mentioned time-frequency conversion process adopts fast Fourier transformer to realize.

To the F behind the time-frequency conversion (f) delivery, and obtain the pairing frequency f of maximum in view of the above ₀With three dB bandwidth B, as the priori spectrum signature of signal x (t), i.e. priori.

According to the above-mentioned priori of obtaining, carry out matched filtering to received signal, output filtering signal s (t)

$s\left(t\right)={\∫}_0^{T}y(t-\mathrm{\τ})h\left(\mathrm{\τ}\right)\mathrm{d\τ}$

Matched filter function h (t) is by priori f ₀Decision, i.e. h (t)=cos [2 π f ₀(T-t)]+sin [2 π f ₀(T-t)], wherein τ is a delay time.

According to the signal F (f) behind the time-frequency conversion and alpha and the bandwidth B set according to the false alarm rate and the false dismissed rate of system requirements, the decision threshold setting apparatus is set decision threshold η

η＝α|F(f)| ²/B

Decision device is exported s (t) according to the decision threshold η that sets to matched filter and is supposed (H ₀And H ₁) check.

If H ₀Set up, receive signal y (t)=n (t), wherein do not contain signal x (t), do not have signal x (t) in the pairing frequency range; If H ₁Set up, receive signal y (t)=x and can use this frequency range to communicate (t)+n (t), then have signal x (t) in this frequency range, the wireless frequency spectrum signal x (t) that distributes (mandate) is promptly arranged, therefore cannot use this frequency range to communicate using this frequency range.

Claims (4)

1. estimate and detection method that based on the signal of nonlinear transformation the wireless frequency spectrum signal that surrounding environment is existed carries out two kinds of hypothesis: do not have wireless frequency spectrum signal H ₀There is wireless frequency spectrum signal H ₁

H ₀：y(t)＝n(t)

H ₁：y(t)＝x(t)+n(t)

N (t) representes additive Gaussian noise, the wireless frequency spectrum signal that x (t) expression has been authorized, and the signal that receives is y (t), whether 0≤t≤T to existing signal x (t) to estimate among the signal y (t) and detecting, is characterized in that comprising the following steps:

1) nonlinear transformation is carried out nonlinear transformation with the broadband signal y that receives (t) through the non-linear converter, obtains nonlinear transformation signal f (t);

2) correlated characteristic of signal is extracted in feature extraction the signal f (t) after nonlinear transformation, and offers matched filter as priori;

3) matched filtering detects, and matched filter is according to step 2) in the priori that draws said reception signal y (t) is carried out matching detection, coupling output result is as the foundation of judgement;

4) judgement, decision device are judged the matched filter testing result according to the decision threshold of setting judge whether there is signal x (t);

Said step 2) obtaining of the said priori in is:

1) the signal f (t) after the nonlinear transformation is carried out time-frequency conversion through fast Fourier transformer and obtain time-frequency conversion signal F (f)

$F\left(f\right)={\∫}_0^{T}f\left(t\right)e^{-j2\mathrm{\πft}}\mathrm{dt};$

2), and obtain the pairing frequency f of maximum in view of the above to the F behind the time-frequency conversion (f) delivery ₀With three dB bandwidth B, as the priori spectrum signature of signal x (t), i.e. priori.

2. the signal based on nonlinear transformation according to claim 1 is estimated and detection method, it is characterized in that the non-linear converter in the said step 1) does

f(t)＝ay ²(t)-by(t-τ ₁)y(t+τ ₂)-cy(t-τ ₃)

Wherein a, b and c are weight coefficient, τ ₁, τ ₂And τ ₃It is respectively time-delay correlation time.

3. the signal based on nonlinear transformation according to claim 1 is estimated and detection method; It is characterized in that said matching detection in the said step 3) be according to said priori through matched filter to received signal y (t) carry out matched filtering, output filtering signal s (t)

$s\left(t\right)={\∫}_0^{T}y(t-\mathrm{\τ})h\left(\mathrm{\τ}\right)\mathrm{d\τ}$

Matched filter function h (t) is by priori f ₀Decision, i.e. h (t)=cos [2 π f ₀(T-t)]+sin [2 π f ₀(T-t)], wherein τ is a delay time.

4. the signal based on nonlinear transformation according to claim 1 is estimated and detection method, it is characterized in that said step 4) decision threshold is set at

η＝α|F(f)| ²/B

Wherein alpha will be set according to the false alarm rate and the false dismissed rate of system requirements,

Decision device detects said output filtering signal s (t) according to above-mentioned decision threshold η, if H ₀Set up, receive signal y (t)=n (t), wherein do not contain signal x (t), can use y (t) corresponding frequency band to communicate; If H ₁Set up, contain signal x (t) in y (t) corresponding frequency band, therefore cannot use the corresponding frequency range of y (t) to communicate.

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