CN106054130A - Indoor positioning method and device based on MUSIC algorithm - Google Patents

Abstract

The invention discloses an indoor positioning method and an indoor positioning device based on a MUSIC algorithm. The indoor positioning method comprises the steps of: setting K receiving antennas to form a signal receiving array and M signal transmitting points; calculating a covariance matrix R<xx> by utilizing a signal matrix outputted by the signal receiving array; constructing a characteristic equation by utilizing the covariance matrix R<xx>, and solving the characteristic equation to obtain a plurality of characteristic values lambda<i> and eigenvectors v<i> corresponding to the characteristic values lambda<i>, and sorting the characteristic values lambda<i>; calculating master variables and number of the master variables of the sorted characteristic values lambda<i> by adopting a principal component analysis method and a set accumulating contribution rate, and acquiring the characteristic value corresponding to a signal subspace and the eigenvector corresponding to a noise subspace; and constructing a spectral function, searching out M maximum spectrum peaks, and calculating a direction of arrival. The indoor positioning method can be in networking communication with a wireless gateway through a beacon point deployed in a monitored region, transmits data to a cloud through a wireless communication module, and carrying out cooperative sensing, acquisition and positioning of information of a signal transmitting point in a network coverage area.

Description

A kind of indoor orientation method based on MUSIC algorithm and device

Technical field

The invention belongs to Internet of Things application, particularly relate to a kind of indoor orientation method based on MUSIC algorithm and dress Put.

Background technology

Developing rapidly with increasingly mature along with technology such as radio communication, integrated circuit and MESH network, feature is empty Between class (MUSIC) algorithm utilize the orthogonality of signal subspace and noise subspace, construct spatial spectrum function, pass through spectrum peak search Determine the direction of arrival (DOA) of signal.Its direction finding principle is the theory according to matrix-eigenvector-decomposition, to array output covariance Matrix R_xxCarrying out feature decomposition, it is empty that the characteristic vector of covariance matrix belongs to one of two orthogonal subspaces, referred to as feature Between (signal subspace) and non-master proper subspace (noise subspace).

But reality is use finite number sample estimate covariance matrix R_xx, all correspond to the spy of noise power Value indicative also differs, but the value that one group of difference is little.Along with in order to estimate R_xxThe increase of sample number, characterize they discrete journeys The variance of degree is gradually reduced, and they will be changed into one group of value relatively, the tuple of minimal eigenvalue once it is determined that, so that it may To determine the estimation number of signal.By finding and R_xxSmall feature value characteristic of correspondence vector closest to orthogonal guiding to Amount, the steering vector can estimated with receive signal correction, the most how different characteristic vector sum eigenvalue is corresponded to difference Subspace be exactly the core of MUSIC algorithm.

Summary of the invention

For the problems referred to above, the present invention proposes a kind of indoor orientation method based on MUSIC algorithm and device, the method energy Enough beacon point and radio network gateway group-net communications by being deployed in monitored area, data are transmitted to cloud through wireless communication module End, carries out collaborative sensing, gathers and position the information of signal launch point in network's coverage area.

Realizing above-mentioned technical purpose, reach above-mentioned technique effect, the present invention is achieved through the following technical solutions:

A kind of indoor orientation method based on MUSIC algorithm, comprises the following steps:

(1) in area to be targeted, dispose K beacon point and constitute signal receiving array；

(2) being made up of M signaling point M wireless mobile apparatus, M wireless mobile apparatus directly enters with signal receiving array Row communication；

(3) signal matrix utilizing signal receiving array to export calculates covariance matrix R_xx；

(4) covariance matrix R is utilized_xxStructural feature equation | λ I-R_xx|=0, solve characteristic equation, obtain multiple feature Value λ_iAnd with eigenvalue characteristic of correspondence vector v_i, and to eigenvalue λ_iCarry out size sequence；

(5) to each eigenvalue λ through sequence_iThe accumulation contribution rate utilizing PCA and setting calculates main transformer Amount and the number of master variable, thus obtain and signal subspace and noise subspace characteristic of correspondence value and characteristic vector respectively, Form signal subspace and noise subspace；

(6) utilize MUSIC algorithm construction spectral function, search out M maximum spectral peak of spectral function, thus calculate the efferent echo side of reaching To, orient the geographical position of M signaling point, M wireless mobile apparatus is by the geographical position of corresponding signaling point and Mac Address is transferred to radio network gateway, radio network gateway be transferred to high in the clouds Surveillance center；

(7) when M wireless mobile apparatus moves to other position, repeated execution of steps (2)～(6), obtain M nothing The new geographical position of line mobile device；

(8) high in the clouds Surveillance center finds out 2 different geographical position with identical Mac address, carries out route planning, and It is sent to wireless mobile apparatus, it is achieved indoor positioning.

In described step (5), in PCA, principal component contributor rate is:

${\mathrm{PC}}_k={\mathrm{\&lambda;}}_k/\underset{i=1}{\overset{k}{\&Sigma;}}{\mathrm{\&lambda;}}_i---\left(1\right)$

Accumulation contribution rate is:

${\mathrm{PA}}_k=\underset{k=1}{\overset{m}{\&Sigma;}}{\mathrm{\&lambda;}}_k/\underset{i=1}{\overset{k}{\&Sigma;}}{\mathrm{\&lambda;}}_i---\left(2\right)$

In formula: m represents under the accumulation contribution rate set, the number of main constituent, m ＜ k.

Spectral function in described step (6) is:

$P=\frac{1}{{V_S}^H{V}_n{V_n}^H{V}_S}---\left(3\right)$

In formula: V_SFor the signal characteristic vector matrix utilizing signal characteristic vector to constitute, V_nFor utilizing noise feature vector structure The noise feature vector matrix become.

Described a kind of based on MUSIC algorithm indoor orientation method, also includes that (9) calculate based on MUSIC algorithm construction The variance of spectral function:

$\mathrm{var}=\frac{{\mathrm{\&sigma;}}_n^2}{T}\frac{\&lsqb;\underset{i=1}{\overset{k}{\&Sigma;}}(\frac{1}{{\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2}+\frac{{\mathrm{\&sigma;}}_n^2}{{({\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2)}^2}){\left|a^H{V}_s\right|}^2\&rsqb;}{\underset{n=1}{\overset{k-M}{\&Sigma;}}{\left|d^H{V}_n\right|}^2}---\left(4\right)$

Wherein d=da/d θ, a=exp [j2 π d (i-1) sin θ] are array steering vector；H represents conjugation means；For connecing Receive array noise variance；T is the scanning cumulative time.

DefinitionThen (4) formula can be written as:

When var value is more than 1, main constituent number is added 1, recalculate accumulation contribution rate PA in formula (2)_k。

A kind of device utilizing indoor orientation method based on MUSIC algorithm, constitutes signal including K beacon point and receives Array, radio network gateway, M wireless mobile apparatus, high in the clouds Surveillance center；Described K beacon point constitutes signal receiving array minute Cloth, in area to be targeted, is radio communication between M wireless mobile apparatus and signal receiving array；Wireless mobile apparatus passes through Wave point is connected with radio network gateway；Radio network gateway sends information and is transferred to high in the clouds control centre, and receives high in the clouds control centre The signal sent.

Described mobile radio terminal is Bluetooth mobile terminal；Described radio network gateway is bluetooth radio network gateway；Described wireless connect Mouth is bluetooth wireless interface.

Beneficial effects of the present invention:

The present invention proposes a kind of indoor orientation method based on MUSIC algorithm and device, by disposing K in area to be targeted Individual beacon point constitutes signal receiving array, utilizes M wireless mobile apparatus to constitute M signaling point, and M signaling point is individual with K Communicating between beacon point, wireless mobile apparatus combines MUSIC location algorithm, PCA obtains direction of arrival information, Thus orient the geographical position of signaling point, its mac address information of wireless mobile apparatus and the geographical location information warp of signaling point Cross radio network gateway and be sent to high in the clouds Surveillance center；When, after M wireless mobile apparatus change of location, again carrying out its physical location Location, and upload the geographical location information of its mac address information and signaling point to high in the clouds Surveillance center；High in the clouds control centre is carried out Route planning, and it is assigned to wireless mobile apparatus by reverse communication link, utilize the navigation of wireless mobile apparatus to realize anti- To seeking position, it is highly suitable for underground garage navigation system.

The present invention proposes a kind of indoor orientation method based on MUSIC algorithm, first finds the letter of signal receiving array output Number covariance matrix R_xxEigenvalue, it is sorted from big to small, utilizes the contribution rate of accumulative total of PCA and setting Calculating the number of master variable and master variable, so that it is determined that go out signal subspace and noise subspace, bind profile function calculates Efferent echo reaches directional information.

The present invention proposes a kind of indoor orientation method based on MUSIC algorithm, has good parameter estimation performance and relatively Little amount of calculation, can obtain the Asymptotic upbiased estimation of parameter, and the method algorithm is simple, it is easy to programming realization.To hits Carry out singular value decomposition according to matrix or the covariance matrix to sampled data carries out Eigenvalues Decomposition, utilize the signal decomposing gained Subspace and the orthogonality of noise subspace, carry out indoor positioning.

Accompanying drawing explanation

Fig. 1 is the schematic flow sheet of the method for the present invention.

Fig. 2 is that in the present invention, signal receiving array receives signal schematic representation.

Fig. 3 is the aisle layout schematic block diagram in the present invention.

Fig. 4 is present invention location simulation figure under white Gaussian noise.

Fig. 5 is the location simulation figure under gaussian colored noise of the present invention.

Detailed description of the invention

In order to make the purpose of the present invention, technical scheme and advantage clearer, below in conjunction with embodiment, to the present invention It is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not used to Limit the present invention.

Below in conjunction with the accompanying drawings the application principle of the present invention is explained in detail.

As it is shown in figure 1, a kind of indoor orientation method based on MUSIC algorithm, comprise the following steps:

(1) in area to be targeted, dispose K beacon point and constitute signal receiving array；

(2) being made up of M signaling point M wireless mobile apparatus, M wireless mobile apparatus directly enters with signal receiving array Row communication；

(3) signal matrix utilizing signal receiving array to export calculates covariance matrix R_xx；

(4) covariance matrix R is utilized_xxStructural feature equation | λ I-R_xx|=0, solve characteristic equation, obtain multiple feature Value λ_iAnd with eigenvalue characteristic of correspondence vector v_i, and to eigenvalue λ_iCarry out size sequence；

(5) to each eigenvalue λ through sequence_iThe accumulation contribution rate utilizing PCA and setting calculates main transformer Amount and the number of master variable, thus obtain and signal subspace and noise subspace characteristic of correspondence value and characteristic vector respectively, Form signal subspace and noise subspace；

(6) utilize MUSIC algorithm construction spectral function, search out M maximum spectral peak of spectral function, thus calculate the efferent echo side of reaching To, orient the geographical position of M signaling point, M wireless mobile apparatus is by the geographical position of corresponding signaling point and Mac Address is transferred to radio network gateway, radio network gateway be transferred to high in the clouds Surveillance center；

(7) when M wireless mobile apparatus moves to other position, repeated execution of steps (2)～(6), obtain M nothing The new geographical position of line mobile device；

(8) high in the clouds Surveillance center finds out 2 different geographical position with identical Mac address, carries out route planning, and It is sent to wireless mobile apparatus, it is achieved indoor positioning.

In described PCA, principal component contributor rate is:

${\mathrm{PC}}_k={\mathrm{\&lambda;}}_k/\underset{i=1}{\overset{k}{\&Sigma;}}{\mathrm{\&lambda;}}_i---\left(1\right)$

Accumulation contribution rate is:

${\mathrm{PA}}_k=\underset{k=1}{\overset{m}{\&Sigma;}}{\mathrm{\&lambda;}}_k/\underset{i=1}{\overset{k}{\&Sigma;}}{\mathrm{\&lambda;}}_i---\left(2\right)$

In formula: m represents when accumulation contribution rate is set to 80%, the number of main constituent, m ＜ k.

Spectral function in described step (6) is:

$P=\frac{1}{{V_S}^H{V}_n{V_n}^H{V}_S}---\left(3\right)$

In formula: V_SFor the signal characteristic vector matrix utilizing signal characteristic vector to constitute, V_nFor utilizing noise feature vector structure The noise feature vector matrix become.

Described a kind of based on MUSIC algorithm indoor orientation method, also includes that (9) calculate based on MUSIC algorithm construction The variance of spectral function:

$\mathrm{var}=\frac{{\mathrm{\&sigma;}}_n^2}{T}\frac{\&lsqb;\underset{i=1}{\overset{k}{\&Sigma;}}(\frac{1}{{\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2}+\frac{{\mathrm{\&sigma;}}_n^2}{{({\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2)}^2}){\left|a^H{V}_s\right|}^2\&rsqb;}{\underset{n=1}{\overset{k-M}{\&Sigma;}}{\left|d^H{V}_n\right|}^2}---\left(4\right)$

Wherein d=da/d θ, a=exp [j2 π d (i-1) sin θ] are array steering vector；H represents conjugation means；For connecing Receiving end noise variance；T is the scanning cumulative time.

DefinitionThen (4) formula can be written as:

When var value is more than 1, main constituent number is added 1, recalculate accumulation contribution rate PA in formula (2)_k。

It can be seen that when array number is abundant, and when signal to noise ratio is the biggest, MUSIC performance is closer to CRB, algorithm estimated accuracy The highest.

Below in conjunction with specific embodiment, the present invention will be described:

As shown in Figures 2 and 3, the present invention includes that beacon (array element) point by K spacing is d constitutes signal receiving array, M Individual signal launch point (stop), corresponding angle of incidence be θ, θ be the angle with normal direction, the noise of each array element is white Gaussian Noise, between each array element, noise is separate, and noise is the most separate with signal.

The covariance matrix R of signal receiving array_xxK eigenvalue and characteristic vector, R can be resolved into_xxCan represent For:

$R_{xx}=\underset{i=1}{\overset{K}{\&Sigma;}}{\mathrm{\&lambda;}}_i{v}_i{v}_i^H={\mathrm{V\&Lambda;V}}^H$

Wherein λ_i, v_iBe respectively eigenvalue and with eigenvalue characteristic of correspondence vector, V is with v_iFor the column matrix of element, Λ It it is the diagonal matrix with eigenvalue as element.Due to uncorrelated between each signal and noise, therefore in all of eigenvalue, main Wanting eigenvalue i.e. signal characteristic value number identical with target number, residue character value is noise；Owing to signal subspace is corresponding big Eigenvalue, and principal component analysis extracts and extracts master variable exactly, after obtaining master variable number, can look for according to eigenvalue number To corresponding noise subspace characteristic vector.According to MUSIC method, direction of arrival can be obtained according to peak value.Therefore exist In Practical Calculation, PCA is used to be used for extracting dominant eigenvalue number.

Therefore above formula can be revised as:

R_xx=V_sΛ_sV_s ^H+V_nΛ_nV_n ^H。

First characteristic equation is solved | λ I-R_xx|=0, thus obtain eigenvalue λ₁,…λ_k, and make its order arrangement by size, Obtain the most respectively corresponding to eigenvalue λ_iCharacteristic vector v_i(i=1,2 ... k).When getting m (m≤k) individual main constituent, main Composition PC_kContribution rate:Accumulation contribution rate:In an embodiment of the present invention, accumulation contribution rate Get 80%.

Said process can be by calling in matlab [PC, latent, explained]=pcacov (X) function to association Variance matrix carries out principal component analysis, returns principal component contributor rate (PC_k), covariance matrix R_xxEigenvalue (latent) and every Individual characteristic vector is characterized in observed quantity population variance shared percent (explained), can calculate tired by percent Meter contribution rate.

After obtaining main constituent number m, according to total characteristic value number, approximate calculation little eigenvalue number can be gone out, thus Calculate signal characteristic vector and noise feature vector, and obtain signal subspace eigenvectors matrix and the noise sky of correspondence Between eigenvectors matrix.

By MUSIC algorithmic formula:

$P=\frac{1}{{V_S}^H{V}_n{V_n}^H{V}_S}$

Wherein V_SAnd V_nIt is respectively signal and noise vector.

By asking for spectral function maximum at space spectral domain, angle corresponding to its spectral peak is i.e. the estimation at arrival bearing angle.

Calculate the variance of spectral function based on MUSIC algorithm construction:

$\mathrm{var}=\frac{{\mathrm{\&sigma;}}_n^2}{T}\frac{\&lsqb;\underset{i=1}{\overset{k}{\&Sigma;}}(\frac{1}{{\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2}+\frac{{\mathrm{\&sigma;}}_n^2}{{({\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2)}^2}){\left|a^H{V}_s\right|}^2\&rsqb;}{\underset{n=1}{\overset{k-M}{\&Sigma;}}{\left|d^H{V}_n\right|}^2}---\left(4\right)$

Wherein d=da/d θ, a=exp [j2 π d (i-1) sin θ] are array steering vector；Subscript H represents conjugation means； For receiving terminal noise variance；T is the scanning cumulative time.

DefinitionThen (4) formula can be written as:

It can be seen that when array number is abundant, and when signal to noise ratio is the biggest, MUSIC performance is closer to CRB, algorithm estimated accuracy The highest.

As shown in Figure 4, the MUSIC location simulation figure under white Gaussian noise, described under white Gaussian noise signal to noise ratio be 20dB, fast umber of beats is 256.As it is shown in figure 5, the MUSIC location simulation figure under gaussian colored noise, described noise power is respectively For [3,3,3,3,16,2,20,80,2,2], mean power is 13.4, and signal to noise ratio is 2dB.

A kind of device utilizing indoor orientation method based on MUSIC algorithm, constitutes signal including K beacon point and receives Array, radio network gateway, M wireless mobile apparatus, high in the clouds Surveillance center；Described K beacon point constitutes signal receiving array minute Cloth, in area to be targeted, is radio communication between M wireless mobile apparatus and signal receiving array；Wireless mobile apparatus passes through Wave point is connected with radio network gateway；Radio network gateway sends information and is transferred to high in the clouds control centre, and receives high in the clouds control centre The signal sent.

In the present invention, radio network gateway is as the main equipment of network, and wireless mobile apparatus such as mobile phone dissipates as from node Cloth, in the communication range specified, constitutes network by MANET mode.

Described mobile radio terminal is Bluetooth mobile terminal；Described radio network gateway is bluetooth radio network gateway；Described wireless connect Mouth is bluetooth wireless interface.

The work process of the device utilizing indoor orientation method based on MUSIC algorithm of the present invention is as follows:

(1) first passing through M wireless mobile apparatus and launch signal, K beacon point constitutes signal receiving array and receives also Feedback information is to wireless mobile apparatus；In area to be targeted, all of wireless mobile apparatus all can directly with each beacon Point communicates, and the MAC Address of each wireless mobile apparatus can be constituted network to conveniently enter and to leave MANET mode；

(2) wireless mobile apparatus carries out location Calculation according to Music algorithm, obtains each wireless mobile apparatus ground this moment Reason positional information, specifically uses step (2)-(5) in indoor orientation method based on MUSIC algorithm, then by wireless The Mac address information of mobile device and wireless mobile apparatus geographical location information this moment, is sent to high in the clouds by radio network gateway Surveillance center, stores；Particularly as follows: local data information is pressed by wireless mobile apparatus by its internal wireless communication module Pack according to the data form set, send packed data to radio network gateway by wave point；Wireless Gateway will transfer data to high in the clouds Surveillance center；

(3) after wireless mobile apparatus changing position, want to find out the position at original place, then calculate again according to Music Method carries out location Calculation, obtains each wireless mobile apparatus geographical location information this moment, then by the Mac of wireless mobile apparatus Address information and wireless mobile apparatus geographical location information this moment, is sent to high in the clouds Surveillance center by radio network gateway, carries out Storage；During particularly as follows: wireless mobile apparatus is remotely controlled by high in the clouds, by various instructions according to the most configured data form Packing, is sent to wireless mobile apparatus by wave point.

(4) high in the clouds Surveillance center is according to the information of storage, finds out 2 different geographical position that identical Mac address is corresponding, Carry out route planning, and be sent to wireless mobile apparatus, it is achieved indoor positioning.

The ultimate principle of the present invention and principal character and advantages of the present invention have more than been shown and described.The technology of the industry Personnel, it should be appreciated that the present invention is not restricted to the described embodiments, simply illustrating this described in above-described embodiment and description The principle of invention, without departing from the spirit and scope of the present invention, the present invention also has various changes and modifications, and these become Change and improvement both falls within scope of the claimed invention.Claimed scope by appending claims and Equivalent defines.

Claims (6)

1. an indoor orientation method based on MUSIC algorithm, it is characterised in that comprise the following steps:

(1) in area to be targeted, dispose K beacon point and constitute signal receiving array；

(2) being made up of M signaling point M wireless mobile apparatus, M wireless mobile apparatus directly leads to signal receiving array Letter；

(3) signal matrix utilizing signal receiving array to export calculates covariance matrix R_xx；

(4) covariance matrix R is utilized_xxStructural feature equation | λ I-R_xx|=0, solve characteristic equation, obtain multiple eigenvalue λ_iWith With eigenvalue characteristic of correspondence vector v_i, and to eigenvalue λ_iCarry out size sequence；

(5) to each eigenvalue λ through sequence_iThe accumulation contribution rate utilizing PCA and setting calculate master variable and The number of master variable, thus obtain and signal subspace and noise subspace characteristic of correspondence value and characteristic vector respectively, formed Signal subspace and noise subspace；

(6) utilize MUSIC algorithm construction spectral function, search out M maximum spectral peak of spectral function, thus calculate direction of arrival, Orienting the geographical position of M signaling point, M wireless mobile apparatus is by the geographical position of corresponding signaling point and Mac ground Location is transferred to radio network gateway, radio network gateway be transferred to high in the clouds Surveillance center；

(7) when M wireless mobile apparatus moves to other position, repeated execution of steps (2)～(6), obtain M wireless shifting The new geographical position of dynamic equipment；

(8) high in the clouds Surveillance center finds out 2 different geographical position with identical Mac address, carries out route planning, and sends To wireless mobile apparatus, it is achieved indoor positioning.

A kind of indoor orientation method based on MUSIC algorithm the most according to claim 1, it is characterised in that: described step (5) in, in PCA, principal component contributor rate is:

${\mathrm{PC}}_k={\mathrm{\&lambda;}}_k/\underset{i=1}{\overset{k}{\&Sigma;}}{\mathrm{\&lambda;}}_i---\left(1\right)$

Accumulation contribution rate is:

${\mathrm{PA}}_k=\underset{k=1}{\overset{m}{\&Sigma;}}{\mathrm{\&lambda;}}_k/\underset{i=1}{\overset{k}{\&Sigma;}}{\mathrm{\&lambda;}}_i---\left(2\right)$

In formula: m represents under the accumulation contribution rate set, the number of main constituent, m ＜ k.

A kind of indoor orientation method based on MUSIC algorithm the most according to claim 1, it is characterised in that: described step (6) spectral function in is:

$P=\frac{1}{{V_S}^H{V}_n{V_n}^H{V}_S}---\left(3\right)$

In formula: V_SFor the signal characteristic vector matrix utilizing signal characteristic vector to constitute, V_nFor utilizing noise feature vector to constitute Noise feature vector matrix.

4., according to a kind of based on MUSIC algorithm the indoor orientation method according to any one of claims 1 to 3, its feature exists In:

Also include (9) calculate spectral function based on MUSIC algorithm construction variance:

$\mathrm{var}=\frac{{\mathrm{\&sigma;}}_n^2}{T}\frac{\&lsqb;\underset{i=1}{\overset{k}{\&Sigma;}}(\frac{1}{{\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2}+\frac{{\mathrm{\&sigma;}}_n^2}{{({\mathrm{\&lambda;}}_i-{\mathrm{\&sigma;}}_n^2)}^2})|a^H{V}_s{|}^2\&rsqb;}{\underset{n=1}{\overset{k-M}{\&Sigma;}}|d^H{V}_n{|}^2}---\left(4\right)$

Wherein d=da/d θ, a=exp [j2 π d (i-1) sin θ] are array steering vector；H represents conjugation means；For receiving battle array Row noise variance；T is the scanning cumulative time.

DefinitionThen (4) formula can be written as:

When the value of var is more than 1, main constituent number is added 1, recalculate accumulation contribution rate PA in formula (2)_k。

5. the device of the indoor orientation method based on MUSIC algorithm utilized described in claim 1, it is characterised in that: bag Include K beacon point and constitute signal receiving array, radio network gateway, M wireless mobile apparatus, high in the clouds Surveillance center；Described K Beacon point constitutes signal receiving array and is distributed in area to be targeted, between M wireless mobile apparatus and signal receiving array For radio communication；Wireless mobile apparatus is connected with radio network gateway by wave point；Radio network gateway sends information and is transferred to high in the clouds Control centre, and receive the signal that high in the clouds control centre sends.

A kind of device utilizing indoor orientation method based on MUSIC algorithm the most according to claim 5, its feature exists In: described mobile radio terminal is Bluetooth mobile terminal；Described radio network gateway is bluetooth radio network gateway；Described wave point is blue Tooth wave point.