CN105487063A - Direct positioning method based on external radiation source time delay and Doppler frequency - Google Patents

Abstract

The invention discloses a direct positioning method based on outer radiation source time delay and Doppler frequency, which overcomes the problem that the prior art does not fully utilize the information of a direct wave signal of an external radiation source. The direct positioning method comprises steps of performing time synchronization on double-channel reception systems of L observation stations, calculating the Fourier coefficient of the data received by the double channels of each observation station, transmitting the obtained array signal frequency domain data to a center station by the observation station, constructing a gauss maximum likelihood function for the data of the conversion value frequency domain and extracting the information matrix containing the echo time delay, the Doppler and the direct wave time delay information. The accurate positioning of the object can be obtained through setting a grid searching scope, calculating the maximum characteristic value corresponding to the data information array on the geography grid and searching the coordinate corresponding to the maximum value in the range of the grid. Compared with the traditional two-step positioning algorithm, the invention reduces the loss of the positioning information, and the positioning accuracy is dramatically improved.

Description

A kind of direct localization method based on external sort algorithm time delay and Doppler frequency

Technical field

This invention relates to the localization method under a kind of external radiation passive location scene, particularly relates to a kind of direct localization method based on external sort algorithm time delay and Doppler frequency.

Background technology

External sort algorithm passive location, refer to the irradiation source utilizing noncooperative third party's radiation source (such as AM/FM signal, common/digital television signal etc.) as target, process by involving reflection echo to going directly, to obtain the correlation parameter such as time delay, frequency information, and then realize the localization and tracking to target.Utilize third-party no-cooperative radiate to detect target, can not only realize, to stealth target and the detection of target of mourning in silence, localization and tracking, equally also may be used for the imaging to target and identification.

The location method that current external sort algorithm passive location adopts is traditional passive location system, i.e. two step location methods, namely first parameter estimation is carried out, as poor in angle of arrival, time of arrival, time of arrival, Doppler frequency difference, received signal strength and many kinds of parameters Combined estimator, then by positioning the location estimation resolved and obtain target to the parameter obtained.Because two traditional step localization methods need the correlation parameter first obtaining target, then the location estimation of target is obtained by separating positioning equation, parameter estimation and positioning calculation are separated, cannot ensure that the positional information of parameter and the real goal measured matches, the error of the parameter that first step measurement simultaneously obtains may be amplified by calculation method further and be difficult to be eliminated, thus cause inevitably there is information loss in whole data handling procedure, so optimum estimated performance cannot be obtained.

Two traditional step location algorithms have the shortcoming of model itself, and positioning performance is limited by the acquisition of parameters precision, makes to locate to there is certain error.Consider that in the data of reception, itself is containing information such as delay parameter, Doppler frequency parameter and target locations, the so direct coordinate parameters from reception extracting data target is also feasible.Therefore, from data, how directly can obtain the study hotspot that target position information just becomes current.

First the people such as A.Dornon analyze deterministic maximum likelihood estimator and Gauss's maximum likelihood estimator module for performance during broadband emission source electricity.A.Weiss is by structure maximum likelihood cost function, the location estimation that two-dimensional search directly obtains target is carried out in the geographic grid of definition, propose a kind of new definition method--the direct location distinguished with two step localization methods, this algorithm can approach a carat Metro lower bound under Low SNR.Parameter estimation and positioning calculation are fused in the middle of a model by DPD algorithm, avoid the information loss in conventional mapping methods; Merge the data message of all research stations in DPD algorithm simultaneously, solve the problem of " data-emissive source association " in Multi-target position.But the direct location algorithm designed by them does not consider concrete location scene, thus decrease the possibility that can increase locating information, improve positioning precision.Outside under Passive Location of Emitter background, each research station is except receiving the echoed signal from target reflection, also to receive the direct-path signal from external sort algorithm, the reception data model of direct-path signal and echoed signal one isostructure higher-dimension can be improved positioning precision effectively.

Summary of the invention

Instant invention overcomes in prior art, under existing external sort algorithm passive location condition, the not enough and existing direct localization method of traditional two step positioning method accuracy is to the problem of external sort algorithm direct-path signal Information Pull deficiency, provides a kind of direct localization method based on external sort algorithm time delay and Doppler frequency.

Technical solution of the present invention is, provides a kind of direct localization method based on external sort algorithm time delay and Doppler frequency with following steps: comprise the following steps:

Step 1: time synchronized is carried out to the dual channel receiver system of L research station, and gather the direct-path signal of external sort algorithm and the echoed signal through target reflection according to Nyquist sampling thheorem, thus obtain the time domain data of multistation reception;

Step 2: its fourier coefficient is calculated respectively to the twin-channel reception data in each station, thus obtains the frequency domain data of multistation Received signal strength;

Step 3: obtained array signal frequency domain data is transferred to central station by each research station, central station by the array signal data of each station transmission according to the order stack arrangement of research station, to construct higher array signal frequency domain data;

Step 4: the information matrix comprising echo time delay, Doppler and direct wave Delay extracts to the data configuration Gauss maximum likelihood function of conversion values frequency domain at central station;

Step 5: by setting grid search scope, and calculate the eigenvalue of maximum that on GEONET lattice point, data information matrix is corresponding;

Step 6: the accurate location to target can be obtained by the coordinate that the maximal value within the scope of search grid is corresponding.

In described step 1, the received signal Model in Time Domain of l research station is

$r_l\left(t\right)=\left[\begin{array}{c}s(t-{\mathrm{\τ}}_{d_l})\\ s(t-{\mathrm{\τ}}_l)e^{j2{\mathrm{\πf}}_{l}t}\end{array}\right]+\left[\begin{array}{c}{w}_{d_l}\left(t\right)\\ w_l\left(t\right)\end{array}\right],$ 0≤t＜T

Wherein, represent the direct path time delay of external sort algorithm relative to l research station; τ _l=(|| p _e-p ₀||+|| p _l-p ₀||)/c represent external sort algorithm irradiate target and reflex to research station produce time delay, c represents signal velocity, || || represent 2 norms; p _efor external sort algorithm position, transmitted signal bandwidth W, p ₀for target location, speed is v=[v _x, v _y] ^t; w _l(t) with represent that average is 0 respectively, variance is σ ²the steady white complex gaussian noise of additivity of direct wave passage and echo channel; f _lrepresent the Doppler frequency between target and research station, it comprises two parts, and a part exposes to the Doppler frequency of order time-stamped signals, the Doppler frequency produced when another part is reflection echo arrival research station, therefore f for external sort algorithm _lcan be expressed as

$f_l\stackrel{\mathrm{\Δ}}{=}\frac{f_c}{c}(\frac{v^T(p_0-p_l)}{\left|\right|p_0-p_l\left|\right|}+\frac{v^T(p_0-p_e)}{\left|\right|p_0-p_e\left|\right|})$

Wherein, p _l=[x _l, y _l] ^t(l=1,2 ..., L) for having twin-channel research station, channel reception from the direct-path signal of external sort algorithm, the echoed signal that a channel reception reflects from target.

In described step 2, the received signal frequency domain model of l research station is

${\tilde{r}}_l\left(f_n\right)=\left[\begin{array}{c}\tilde{s}\left(f_n\right)e^{-j2{\mathrm{\πf}}_n{\mathrm{\τ}}_{d_l}}\\ \tilde{s}(f_n-f_l)e^{-j2{\mathrm{\πf}}_n{\mathrm{\τ}}_l}\end{array}\right]+\left[\begin{array}{c}{\tilde{w}}_{d_l}\left(f_n\right)\\ {\tilde{w}}_l\left(f_n\right)\end{array}\right]$

Wherein, ${\tilde{r}}_l\left(f_n\right),\tilde{s}\left(f_n\right),{\tilde{w}}_{d_l}\left(f_n\right)$ With ${\tilde{w}}_l\left(f_n\right)(f_n=n/T,n=\±1,\±2,\mathrm{...})$ Represent Received signal strength respectively, transmit and the fourier coefficient of noise.

In described step 3, the higher-dimension signal frequency domain model that central station obtains is

${\tilde{r}}_l=\left[\begin{array}{c}{\tilde{A}}_l{\tilde{F}}_l\\ {\tilde{B}}_l\end{array}\right]\tilde{s}+\left[\begin{array}{c}{\tilde{w}}_{d_l}\\ {\tilde{w}}_l\end{array}\right]$

Wherein,

$\left\{\begin{array}{c}{\tilde{r}}_l={\[{\tilde{r}}_l\left(f_{-N}\right),{\tilde{r}}_l\left(f_{-N+1}\right),\mathrm{...},{\tilde{r}}_l\left(f_N\right)\]}^T\\ \tilde{s}={\[\tilde{s}\left(f_{-N}\right),\tilde{s}\left(f_{-N+1}\right),\mathrm{...},\tilde{s}\left(f_N\right)\]}^T\\ {\tilde{B}}_l=diag\{e^{-j2{\mathrm{\πf}}_{-N}{\mathrm{\τ}}_{d_l}},e^{-j2{\mathrm{\πf}}_{-N+1}{\mathrm{\τ}}_{d_l}},\mathrm{...},e^{-j2{\mathrm{\πf}}_N{\mathrm{\τ}}_{d_l}}\}\\ {\tilde{A}}_l=diag\{e^{-j2{\mathrm{\πf}}_{-N}{\mathrm{\τ}}_l},e^{-j2{\mathrm{\πf}}_{-N+1}{\mathrm{\τ}}_l},\mathrm{...},e^{-j2{\mathrm{\πf}}_N{\mathrm{\τ}}_l}\}\\ {\tilde{w}}_l={\[{\tilde{w}}_l\left(f_{-N}\right),{\tilde{w}}_l\left(f_{-N+1}\right),\mathrm{...},{\tilde{w}}_l\left(f_N\right)\]}^T\\ {\tilde{w}}_{d_l}={\[{\tilde{w}}_{d_l}\left(f_{-N}\right),{\tilde{w}}_{d_l}\left(f_{-N+1}\right),\mathrm{...},{\tilde{w}}_{d_l}\left(f_N\right)\]}^T\end{array}\right.$

In formula, represent cyclic shift matrices, its form is as follows, to be shifted downwards floor (Tf by unit matrix circulation _l)+1 row, its effect is to represent the Doppler shift being in Data Position; by matrix circulate the floor (Tf that is shifted downwards by row _l), floor () expression rounds downwards,

In described step 4, Gauss's maximum likelihood function of structure is

${\hat{p}}_0=\arg \underset{p_0}{\min }\underset{l=1}{\overset{L}{\Σ}}\left|\right|{\tilde{r}}_l-\left(\begin{array}{c}{\tilde{A}}_l{\tilde{F}}_l\\ {\tilde{B}}_l\end{array}\right)\tilde{s}|{|}^2$

Simplifying through deriving, following form can be obtained

$\begin{array}{c}{C}_1=\underset{l=1}{\overset{L}{\Σ}}\left|\right|{\tilde{r}}_l-\frac{1}{2}{\left({\tilde{Q}}_l\tilde{s}\right)}^H{\tilde{r}}_l{\tilde{Q}}_l\tilde{s}|{|}^2\\ =\underset{l=1}{\overset{L}{\Σ}}\left|\right|{\tilde{r}}_l|{|}^2-\frac{1}{\sqrt{2}}|{\left({\tilde{Q}}_l\tilde{s}\right)}^H{\tilde{r}}_l{|}^2\end{array}$

Wherein, ${\tilde{Q}}_l={({\tilde{F}}_l^T{\tilde{A}}_l^T,{\tilde{B}}_l^T)}^T;$ Information matrix is

Q _c＝VV ^H

$V=\[\left(\begin{array}{cc}{\tilde{A}}_1^H{\tilde{F}}_1^H& {\tilde{B}}_1^H\end{array}\right){\tilde{r}}_1,\left(\begin{array}{cc}{\tilde{A}}_2^H{\tilde{F}}_2^H& {\tilde{B}}_2^H\end{array}\right){\tilde{r}}_2,\mathrm{...},\left(\begin{array}{cc}{\tilde{A}}_L^H{\tilde{F}}_L^H& {\tilde{B}}_L^H\end{array}\right){\tilde{r}}_L\].$

In described step 5, the eigenvalue of maximum that on GEONET lattice point, data information matrix is corresponding is C ₃=λ _max(Q _c), Q _cdimension be (2N+1) × (2N+1), and when extend observation time time can increase Q further _cdimension, ask eigenwert to substantially increase operand to its Eigenvalues Decomposition; Consider to set matrix X, X ^hx and XX ^hnonzero eigenvalue be consistent, therefore this conclusion can be utilized C ₃be transformed to

$C_3={\mathrm{\λ}}_{max}\left({\stackrel{\‾}{Q}}_c\right),$ In formula, ${\stackrel{\‾}{Q}}_c=V^{H}V.$

In described step 6, obtain by grid search the estimation that coordinate corresponding to the maximal value of cost function is target location

${\hat{p}}_0=\arg \underset{p_0}{\max }{\mathrm{\λ}}_{max}\left({\stackrel{\‾}{Q}}_c\right).$

Compared with prior art, the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency has the following advantages: time domain data is changed into frequency domain data by the fourier coefficient first by calculating Received signal strength, then to the reception data construct Gauss maximum likelihood estimator module being converted to frequency domain, again the problem from extracting data target position information is converted into the problem of the eigenvalue of maximum solving information matrix, obtains the estimation of target location finally by geographic grid search.Compared with two traditional step location algorithms, method provided by the invention directly utilizes reception bottom data to carry out location estimation, avoid because parameter estimation is separated with location compute and cause measurement parameter can not ensure the problem of mating with actual position, decrease the loss of locating information, positioning precision obviously promotes and approaches carat Metro lower bound further and have good robustness to the situation that research station has a different signal to noise ratio (S/N ratio).

Compared to traditional two step localization methods and existing direct localization method, direct wave information and the target reflection echo information of external sort algorithm are considered, construct the multi-dimensional signal model comprising time delay and doppler information, receiving data by utilizing bottom directly to estimate target location, obtaining higher positioning precision and research station being had to the robustness of different signal to noise ratio (S/N ratio).Localization method disclosed by the invention has simple, the efficient feature of realization, is a kind of Robust Performance, reliably high-precision locating method.

Accompanying drawing explanation

Fig. 1 is that in the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency, two step location methods and direct location method contrast schematic diagram;

Fig. 2 is the schematic diagram of a kind of external sort algorithm passive location scene in the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency;

Fig. 3 is the direct positioning principle block diagram of combining time delay and Doppler under the direct localization method China and foreign countries Passive Location of Emitter scene that the present invention is based on external sort algorithm time delay and Doppler frequency;

Fig. 4 is located instance scene schematic diagram in the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency;

Fig. 5 is the pseudo-spectrogram of grid of directly localization method in the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency;

Fig. 6 is the change curve of position root-mean-square error with signal to noise ratio (S/N ratio) of distinct methods in the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency;

Fig. 7 is the change curve of position root-mean-square error with research station quantity of distinct methods in the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency.

Embodiment

Below in conjunction with the drawings and specific embodiments, the direct localization method that the present invention is based on external sort algorithm time delay and Doppler frequency is described further: as shown in the figure, the present embodiment is in order to solve the problem, need the mathematical model of the echoed signal first setting up direct-path signal and the target reflection comprising external sort algorithm, based on this, by the fourier coefficient calculating Received signal strength, time domain data is changed into frequency domain data, then to the reception data construct Gauss maximum likelihood estimator module being converted to frequency domain, again the problem from extracting data target position information is converted into the problem of the eigenvalue of maximum solving information matrix, the estimation of target location is obtained finally by geographic grid search.The concrete implementation step of the present invention is as follows:

The direct localization method of combining time delay and Doppler under external sort algorithm passive location scene disclosed by the invention needs each receiving station to receive from the direct-path signal of external sort algorithm and the echoed signal that reflects through target, the data of conversion values frequency domain can be transferred to central station by each research station, and central station carries out location estimation by utilizing these bottom datas to target.

As shown in Figure 3, the direct localization method of combining time delay and Doppler under external sort algorithm passive location scene disclosed by the invention comprises the following steps:

Step 1: time synchronized is carried out to the dual channel receiver system of L research station, and gather the direct-path signal of external sort algorithm and the echoed signal through target reflection according to Nyquist sampling thheorem, thus obtain the time domain data of multistation reception.

Step 2: its fourier coefficient is calculated respectively to the twin-channel reception data in each station, thus obtains the frequency domain data of multistation Received signal strength.

Step 3: obtained array signal frequency domain data is transferred to central station by each research station, central station by the array signal data of each station transmission according to the order stack arrangement of research station, to construct higher array signal frequency domain data.

Step 4: the information matrix comprising echo time delay, Doppler and direct wave Delay extracts to the data configuration Gauss maximum likelihood function of conversion values frequency domain at central station.

Step 5: by setting grid search scope, and calculate the eigenvalue of maximum that on GEONET lattice point, data information matrix is corresponding.

Step 6: the accurate location to target can be obtained by the coordinate that the maximal value within the scope of search grid is corresponding.

In described step 1, the received signal Model in Time Domain of l research station is

$r_l\left(t\right)=\left[\begin{array}{c}s(t-{\mathrm{\τ}}_{d_l})\\ s(t-{\mathrm{\τ}}_l)e^{j2{\mathrm{\πf}}_{l}t}\end{array}\right]+\left[\begin{array}{c}{w}_{d_l}\left(t\right)\\ w_l\left(t\right)\end{array}\right],$ 0≤t＜T

Wherein, represent the direct path time delay of external sort algorithm relative to l research station; τ _l=(|| p _e-p ₀||+|| p _l-p ₀||)/c represent external sort algorithm irradiate target and reflex to research station produce time delay, c represents signal velocity, || || represent 2 norms; p _efor external sort algorithm position, transmitted signal bandwidth W, p ₀for target location, speed is v=[v _x, v _y] ^t; w _l(t) with represent that average is 0 respectively, variance is σ ²the steady white complex gaussian noise of additivity of direct wave passage and echo channel; f _lrepresent the Doppler frequency between target and research station, it comprises two parts, and a part exposes to the Doppler frequency of order time-stamped signals, the Doppler frequency produced when another part is reflection echo arrival research station, therefore f for external sort algorithm _lcan be expressed as

$f_l\stackrel{\mathrm{\Δ}}{=}\frac{f_c}{c}(\frac{v^T(p_0-p_l)}{\left|\right|p_0-p_l\left|\right|}+\frac{v^T(p_0-p_e)}{\left|\right|p_0-p_e\left|\right|})$

Wherein, p _l=[x _l, y _l] ^t(l=1,2 ..., L) for having twin-channel research station, channel reception from the direct-path signal of external sort algorithm, the echoed signal that a channel reception reflects from target;

In described step 2, the received signal frequency domain model of l research station is

${\tilde{r}}_l\left(f_n\right)=\left[\begin{array}{c}\tilde{s}\left(f_n\right)e^{-j2{\mathrm{\πf}}_n{\mathrm{\τ}}_{d_l}}\\ \tilde{s}(f_n-f_l)e^{-j2{\mathrm{\πf}}_n{\mathrm{\τ}}_l}\end{array}\right]+\left[\begin{array}{c}{\tilde{w}}_{d_l}\left(f_n\right)\\ {\tilde{w}}_l\left(f_n\right)\end{array}\right]$

Wherein, ${\tilde{r}}_l\left(f_n\right),\tilde{s}\left(f_n\right),{\tilde{w}}_{d_l}\left(f_n\right)$ With ${\tilde{w}}_l\left(f_n\right)(f_n=n/T,n=\±1,\±2,\mathrm{...})$ Represent Received signal strength respectively, transmit and the fourier coefficient of noise;

In described step 3, the higher-dimension signal frequency domain model that central station obtains is

${\tilde{r}}_l=\left[\begin{array}{c}{\tilde{A}}_l{\tilde{F}}_l\\ {\tilde{B}}_l\end{array}\right]\tilde{s}+\left[\begin{array}{c}{\tilde{w}}_{d_l}\\ {\tilde{w}}_l\end{array}\right]$

Wherein,

$\left\{\begin{array}{c}{\tilde{r}}_l={\[{\tilde{r}}_l\left(f_{-N}\right),{\tilde{r}}_l\left(f_{-N+1}\right),\mathrm{...},{\tilde{r}}_l\left(f_N\right)\]}^T\\ \tilde{s}={\[\tilde{s}\left(f_{-N}\right),\tilde{s}\left(f_{-N+1}\right),\mathrm{...},\tilde{s}\left(f_N\right)\]}^T\\ {\tilde{B}}_l=diag\{e^{-j2{\mathrm{\πf}}_{-N}{\mathrm{\τ}}_{d_l}},e^{-j2{\mathrm{\πf}}_{-N+1}{\mathrm{\τ}}_{d_l}},\mathrm{...},e^{-j2{\mathrm{\πf}}_N{\mathrm{\τ}}_{d_l}}\}\\ {\tilde{A}}_l=diag\{e^{-j2{\mathrm{\πf}}_{-N}{\mathrm{\τ}}_l},e^{-j2{\mathrm{\πf}}_{-N+1}{\mathrm{\τ}}_l},\mathrm{...},e^{-j2{\mathrm{\πf}}_N{\mathrm{\τ}}_l}\}\\ {\tilde{w}}_l={\[{\tilde{w}}_l\left(f_{-N}\right),{\tilde{w}}_l\left(f_{-N+1}\right),\mathrm{...},{\tilde{w}}_l\left(f_N\right)\]}^T\\ {\tilde{w}}_{d_l}={\[{\tilde{w}}_{d_l}\left(f_{-N}\right),{\tilde{w}}_{d_l}\left(f_{-N+1}\right),\mathrm{...},{\tilde{w}}_{d_l}\left(f_N\right)\]}^T\end{array}\right.$

In formula, represent cyclic shift matrices, its form is as follows, to be shifted downwards floor (Tf by unit matrix circulation _l)+1 row, its effect is to represent the Doppler shift being in Data Position; by matrix circulate the floor (Tf that is shifted downwards by row _l), floor () expression rounds downwards.

In described step 4, Gauss's maximum likelihood function of structure is

${\hat{p}}_0=\arg \underset{p_0}{\min }\underset{l=1}{\overset{L}{\Σ}}\left|\right|{\tilde{r}}_l-\left(\begin{array}{c}{\tilde{A}}_l{\tilde{F}}_l\\ {\tilde{B}}_l\end{array}\right)\tilde{s}|{|}^2$

Simplifying through deriving, following form can be obtained

$\begin{array}{c}{C}_1=\underset{l=1}{\overset{L}{\Σ}}\left|\right|{\tilde{r}}_l-\frac{1}{2}{\left({\tilde{Q}}_l\tilde{s}\right)}^H{\tilde{r}}_l{\tilde{Q}}_l\tilde{s}|{|}^2\\ =\underset{l=1}{\overset{L}{\Σ}}\left|\right|{\tilde{r}}_l|{|}^2-\frac{1}{\sqrt{2}}|{\left({\tilde{Q}}_l\tilde{s}\right)}^H{\tilde{r}}_l{|}^2\end{array}$

Wherein, ${\tilde{Q}}_l={({\tilde{F}}_l^T{\tilde{A}}_l^T,{\tilde{B}}_l^T)}^T;$

Information matrix is

Q _c＝VV ^H

$V=\[\left(\begin{array}{cc}{\tilde{A}}_1^H{\tilde{F}}_1^H& {\tilde{B}}_1^H\end{array}\right){\tilde{r}}_1,\left(\begin{array}{cc}{\tilde{A}}_2^H{\tilde{F}}_2^H& {\tilde{B}}_2^H\end{array}\right){\tilde{r}}_2,\mathrm{...},\left(\begin{array}{cc}{\tilde{A}}_L^H{\tilde{F}}_L^H& {\tilde{B}}_L^H\end{array}\right){\tilde{r}}_L\]$

In described step 5, the eigenvalue of maximum that on GEONET lattice point, data information matrix is corresponding is

C ₃＝λ _max(Q _c)

Notice Q _cdimension be (2N+1) × (2N+1), and when extend observation time time can increase Q further _cdimension, ask eigenwert to substantially increase operand to its Eigenvalues Decomposition.Consider to set matrix X, X ^hx and XX ^hnonzero eigenvalue be consistent, therefore this conclusion can be utilized C ₃be transformed to

$C_3={\mathrm{\λ}}_{max}\left({\stackrel{\‾}{Q}}_c\right)$

In formula, now dimension only have L × L tie up and only relevant with research station quantity, can operand be significantly reduced.

In described step 6, obtain by grid search the estimation that coordinate corresponding to the maximal value of cost function is target location

${\hat{p}}_0=\arg \underset{p_0}{\max }{\mathrm{\λ}}_{max}\left({\stackrel{\‾}{Q}}_c\right)$

External sort algorithm position (-3500m, 3500m), the carrier frequency that transmits is f _c=10 ⁹hz, bandwidth is the gaussian signal of 300kHz, and its velocity of propagation is c=3 × 10 ⁸; Target location (3200m, 3200m), speed v=[260,120] ^t.Choose 5 research stations, position is distributed as (1000m, 4500m) successively, (500m, 2000m), (3000m, 5500m), (4200m, 1500m) with (5500m, 2500m), its geographic distribution as shown in Figure 4.Each research station is 1us to signal observation time, and sample frequency is 10 ⁶hz, namely sampling number is 1000 points.

Fig. 5 gives a kind of directly locating pseudo-spectrogram, and in this figure, each station receives direct wave signal to noise ratio (S/N ratio) and is set to 30dB, receives echo signal to noise ratio (S/N ratio) (SignalNoiseRatio, SNR) and is set as respectively [5dB, 0dB, 3dB ,-5dB, 0dB].Can finding out to have in target location and significantly compose peak, the estimation of target location can be obtained by obtaining coordinate corresponding to spectrum peak.

Fig. 6 compares performance when direct location algorithm and traditional two step location algorithms change with signal to noise ratio (S/N ratio), wherein, two step location algorithms are, first ambiguity function is utilized to estimate time delay and the Doppler frequency information of Received signal strength, recycling Taylor progression iteration obtains the location estimation of target, target location initial value is set to the random Gaussian that locations of real targets secondary power is the theoretical value of the lower 2 times of Cramér-Rao lower bound of corresponding signal to noise ratio (S/N ratio), and iterations is 10 times, and wherein reference station is chosen as station 1.Direct location algorithm hunting zone is the scope of goal-orientation is the rectangular area of 800m.For the ease of contrast, the signal to noise ratio (S/N ratio) setting all research stations is consistent and changes simultaneously, simulation times 100 times.As can be seen from the figure, direct location algorithm positioning precision under the condition of low signal-to-noise ratio is far superior to two traditional step location algorithms, and can CRB be reached when comparatively high s/n ratio, mainly because, Taylor Series Method realizes positioning calculation by ignoring higher order term approximate linearization positioning equation on the one hand, easily do not restrain when comparatively low signal-to-noise ratio, thus produce comparatively big error;

On the other hand, signal to noise ratio (S/N ratio) also have impact on the precision of time delay and Doppler frequency parameter acquiring to a great extent, and the error of parameter estimation is amplified further when location compute, thus causes the poor-performing of two step location algorithms.Directly location utilizes the estimation receiving the direct realize target position of data construct maximum likelihood estimator module, avoid parameter estimation to be separated with location compute and the approximate information loss caused in location compute process, thus effectively improve the estimated accuracy of location.

Consider that research station quantity is on the impact of algorithm performance.The basis of existing research station increases several research station again, and its position coordinates is: (500m, 3000m), (5200m, 4200m), (2500m, 1500m) and (3100m, 4500m).Fig. 7 reflects signal to noise ratio (S/N ratio) under-5dB condition, and when research station adds in positioning system successively, the positioning performance of each algorithm compares.As can be seen from the figure, along with the increase of research station quantity, positioning error constantly reduces.Wherein algorithm is optimum herein, can reach CRB when research station quantity reaches 7.

Impact on positioning performance when considering that different research stations Received signal strength is different signal to noise ratio (S/N ratio).Table 1 compares the positioning result of direct location algorithm and two step location algorithms when each station is different signal to noise ratio (S/N ratio), and under the signal to noise ratio (S/N ratio) of different situations, error gets the average result of 50 times.As can be seen from the table, when each station signal to noise ratio (S/N ratio) is different, compared to Taylor Series Method, direct location algorithm robustness is stronger.Be reference station owing to choosing the 1st research station in Taylor Series Method, therefore the impact of received signal to noise ratio on algorithm performance at the 1st station is larger.To be reflected in table in the 3rd, 4 group of data, when the signal to noise ratio (S/N ratio) at same existence two station is-10dB, the to-noise ratio at the 1st station is larger to location precision, because now different station needs to obtain the time difference and Doppler frequency difference parameter by reference to station, and the received signal quality of reference station directly affects the acquisition of all the other parameters of respectively standing.On the contrary, direct location algorithm is by carrying out searching for the estimation of acquisition target location to respectively standing in the puppet spectrum formed in geographic grid, if the reception data that there is research station can form spectrum peak, can realize location, therefore directly location algorithm has good robustness to the situation that research station has different signal to noise ratio (S/N ratio).

Difference location algorithm Performance comparision when each station of table 1 has a different signal to noise ratio (S/N ratio)

Claims (7)

1., based on a direct localization method for external sort algorithm time delay and Doppler frequency, it is characterized in that: the method comprises the following steps:

Step 1: time synchronized is carried out to the dual channel receiver system of L research station, and gather the direct-path signal of external sort algorithm and the echoed signal through target reflection according to Nyquist sampling thheorem, thus obtain the time domain data of multistation reception;

Step 2: its fourier coefficient is calculated respectively to the twin-channel reception data in each station, thus obtains the frequency domain data of multistation Received signal strength;

Step 3: obtained array signal frequency domain data is transferred to central station by each research station, central station by the array signal data of each station transmission according to the order stack arrangement of research station, to construct higher array signal frequency domain data;

Step 4: the information matrix comprising echo time delay, Doppler and direct wave Delay extracts to the data configuration Gauss maximum likelihood function of conversion values frequency domain at central station;

Step 5: by setting grid search scope, and calculate the eigenvalue of maximum that on GEONET lattice point, data information matrix is corresponding;

Step 6: the accurate location to target can be obtained by the coordinate that the maximal value within the scope of search grid is corresponding.

2. the direct localization method based on external sort algorithm time delay and Doppler frequency according to claim 1, it is characterized in that: in described step 1, the received signal Model in Time Domain of l research station is

$r_l\left(t\right)=\left[\begin{array}{c}s(t-{\mathrm{\&tau;}}_{d_l})\\ s(t-{\mathrm{\&tau;}}_l)e^{j2{\mathrm{\&pi;f}}_{l}t}\end{array}\right]+\left[\begin{array}{c}{w}_{d_l}\left(t\right)\\ w_l\left(t\right)\end{array}\right],0\&le;t<T$

Wherein, represent the direct path time delay of external sort algorithm relative to l research station; τ _l=(|| p _e-p ₀||+|| p _l-p ₀||)/c represent external sort algorithm irradiate target and reflex to research station produce time delay, c represents signal velocity, || || represent 2 norms; p _efor external sort algorithm position, transmitted signal bandwidth W, p ₀for target location, speed is v=[v _x, v _y] ^t; w _l(t) with represent that average is 0 respectively, variance is σ ²the steady white complex gaussian noise of additivity of direct wave passage and echo channel; f _lrepresent the Doppler frequency between target and research station, it comprises two parts, and a part exposes to the Doppler frequency of order time-stamped signals, the Doppler frequency produced when another part is reflection echo arrival research station, therefore f for external sort algorithm _lcan be expressed as

$f_l\stackrel{\mathrm{\&Delta;}}{=}\frac{f_c}{c}(\frac{v^T(p_0-p_l)}{\left|\right|p_0-p_l\left|\right|}+\frac{v^T(p_0-p_e)}{\left|\right|p_0-p_e\left|\right|})$

Wherein, p _l=[x _l, y _l] ^t(l=1,2 ..., L) for having twin-channel research station, channel reception from the direct-path signal of external sort algorithm, the echoed signal that a channel reception reflects from target.

3. the direct localization method based on external sort algorithm time delay and Doppler frequency according to claim 1, it is characterized in that: in described step 2, the received signal frequency domain model of l research station is

${\tilde{r}}_l\left(f_n\right)=\left[\begin{array}{c}\tilde{s}\left(f_n\right)e^{-j2{\mathrm{\&pi;f}}_n{\mathrm{\&tau;}}_{d_l}}\\ \tilde{s}(f_n-f_l)e^{-j2{\mathrm{\&pi;f}}_n{\mathrm{\&tau;}}_l}\end{array}\right]+\left[\begin{array}{c}{\tilde{w}}_{d_l}\left(f_n\right)\\ {\tilde{w}}_l\left(f_n\right)\end{array}\right]$

Wherein, with (f _n=n/T, n=± 1, ± 2 ...) represent Received signal strength respectively, transmit and the fourier coefficient of noise.

4. the direct localization method based on external sort algorithm time delay and Doppler frequency according to claim 1, it is characterized in that: in described step 3, the higher-dimension signal frequency domain model that central station obtains is

${\tilde{r}}_l=\left[\begin{array}{c}{\tilde{A}}_l{\tilde{F}}_l\\ {\tilde{B}}_l\end{array}\right]\tilde{s}+\left[\begin{array}{c}{\tilde{w}}_{d_l}\\ {\tilde{w}}_l\end{array}\right]$

Wherein,

$\left\{\begin{array}{c}{\tilde{r}}_l={\&lsqb;{\tilde{r}}_l\left(f_{-N}\right),{\tilde{r}}_l\left(f_{-N+1}\right),\mathrm{...},{\tilde{r}}_l\left(f_N\right)\&rsqb;}^T\\ \tilde{s}={\&lsqb;\tilde{s}\left(f_{-N}\right),\tilde{s}\left(f_{-N+1}\right),\mathrm{...},\tilde{s}\left(f_N\right)\&rsqb;}^T\\ {\tilde{B}}_l=diag\left\{e^{-j2{\mathrm{\&pi;f}}_{-N}{\mathrm{\&tau;}}_{d_l}},e^{-j2{\mathrm{\&pi;f}}_{-N+1}{\mathrm{\&tau;}}_{d_l}},\mathrm{...},e^{-j2{\mathrm{\&pi;f}}_N{\mathrm{\&tau;}}_{d_l}}\right\}\\ {\tilde{A}}_l=diag\left\{e^{-j2{\mathrm{\&pi;f}}_{-N}{\mathrm{\&tau;}}_l},e^{-j2{\mathrm{\&pi;f}}_{-N+1}{\mathrm{\&tau;}}_l},\mathrm{...},e^{-j2{\mathrm{\&pi;f}}_N{\mathrm{\&tau;}}_l}\right\}\\ {\tilde{w}}_l={\&lsqb;{\tilde{w}}_l\left(f_{-N}\right),{\tilde{w}}_l\left(f_{-N+1}\right),\mathrm{...},{\tilde{w}}_l\left(f_N\right)\&rsqb;}^T\\ {\tilde{w}}_{d_l}={\&lsqb;{\tilde{w}}_{d_l}\left(f_{-N}\right),{\tilde{w}}_{d_l}\left(f_{-N+1}\right),\mathrm{...},{\tilde{w}}_{d_l}\left(f_N\right)\&rsqb;}^T\end{array}\right.$

In formula, represent cyclic shift matrices, its form is as follows, to be shifted downwards floor (Tf by unit matrix circulation _l)+1 row, its effect is to represent the Doppler shift being in Data Position; by matrix circulate the floor (Tf that is shifted downwards by row _l), floor () expression rounds downwards,

5. the direct localization method based on external sort algorithm time delay and Doppler frequency according to claim 1, it is characterized in that: in described step 4, Gauss's maximum likelihood function of structure is

${\hat{p}}_0=\arg \underset{p_0}{min}\underset{l=1}{\overset{L}{\&Sigma;}}\left|\right|{\tilde{r}}_l-\left(\begin{array}{c}{\tilde{A}}_l{\tilde{F}}_l\\ {\tilde{B}}_l\end{array}\right)\tilde{s}|{|}^2$

Simplifying through deriving, following form can be obtained

$C_1=\underset{l=1}{\overset{L}{\&Sigma;}}\left|\right|{\tilde{r}}_l-\frac{1}{2}{\left({\tilde{Q}}_l\tilde{s}\right)}^H{\tilde{r}}_l{\tilde{Q}}_l\tilde{s}|{|}^2$

$=\underset{l=1}{\overset{L}{\&Sigma;}}\left|\right|{\tilde{r}}_l|{|}^2-\frac{1}{\sqrt{2}}{\left|{\left({\tilde{Q}}_l\tilde{s}\right)}^H{\tilde{r}}_l\right|}^2$

Wherein, ${\tilde{Q}}_l={({\tilde{F}}_l^T{\tilde{A}}_l^T,{\tilde{B}}_l^T)}^T;$ Information matrix is

Q _c＝VV ^H

$V=\&lsqb;\left(\begin{array}{cc}{\tilde{A}}_1^H{\tilde{F}}_1^H& {\tilde{B}}_1^H\end{array}\right){\tilde{r}}_1,\left(\begin{array}{cc}{\tilde{A}}_2^H{\tilde{F}}_2^H& {\tilde{B}}_2^H\end{array}\right){\tilde{r}}_2,...,\left(\begin{array}{cc}{\tilde{A}}_L^H{\tilde{F}}_L^H& {\tilde{B}}_L^H\end{array}\right){\tilde{r}}_L\&rsqb;.$

6. the direct localization method based on external sort algorithm time delay and Doppler frequency according to claim 1, it is characterized in that: in described step 5, the eigenvalue of maximum that on GEONET lattice point, data information matrix is corresponding is C ₃=λ _max(Q _c), Q _cdimension be (2N+1) × (2N+1), and when extend observation time time can increase Q further _cdimension, ask eigenwert to substantially increase operand to its Eigenvalues Decomposition; Consider to set matrix X, X ^hx and XX ^hnonzero eigenvalue be consistent, therefore this conclusion can be utilized C ₃be transformed to

$C_3={\mathrm{\&lambda;}}_{max}\left({\stackrel{\&OverBar;}{Q}}_c\right),$ In formula, ${\stackrel{\&OverBar;}{Q}}_c=V^{H}V.$

7. the direct localization method based on external sort algorithm time delay and Doppler frequency according to claim 1, is characterized in that: in described step 6, obtains by grid search the estimation that coordinate corresponding to the maximal value of cost function is target location

${\hat{p}}_0=\arg \underset{p_0}{max}{\mathrm{\&lambda;}}_{max}\left({\stackrel{\&OverBar;}{Q}}_c\right).$