CN112269160A - Multi-information-source direct positioning method based on unmanned aerial vehicle loading nested array - Google Patents
Multi-information-source direct positioning method based on unmanned aerial vehicle loading nested array Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
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Abstract
The invention discloses a multi-information-source direct positioning method based on an unmanned aerial vehicle loading nested array, which comprises the steps that the unmanned aerial vehicle receives a plurality of radiation source signals at different positions and samples the received signals; respectively calculating a received signal sampling covariance matrix of each position, and carrying out vectorization processing on the received signal sampling covariance matrix; fusing the vectorized observation signals to obtain processed virtual receiving signals; and constructing a loss function of the position estimation by adopting a direct correlation method, and obtaining a final radiation source position estimation result through grid search. The method can effectively avoid the secondary loss of the position information, improve the positioning accuracy, realize the simultaneous positioning of multiple information sources without additional information matching, break through the limitation of the freedom degree of the array antenna and realize the simultaneous positioning of the multiple information sources when the number of the information sources is greater than the number of the array elements.
Description
Technical Field
The invention relates to the technical field of passive positioning, in particular to a multi-source direct positioning method based on an unmanned aerial vehicle loading nested array.
Background
Aiming at the problem of radiation source positioning, most of the traditional ground investigation modes are based on ground moving vehicles, and the traditional ground investigation modes are combined with handheld equipment, so that a large amount of manpower and material resources are needed, the traditional ground investigation modes are limited by the influence of complex environments and obstacles, the positioning accuracy is low, the positioning time is long, and the traditional ground investigation modes are very limited in practical application. Compare in ground platform, aerial platform based on unmanned aerial vehicle possess not influenced by ground complex environment, observation scope is wide, the advantage that the flexibility is strong. Therefore, the research of the positioning of the radiation source based on the unmanned aerial vehicle has very important engineering application value.
However, because of the dependence on the estimation of intermediate parameters such as the signal arrival angle, the signal arrival time difference and the like, the traditional two-step positioning technology is difficult to obtain the asymptotically optimal estimation precision, and the success or failure of the intermediate parameter estimation directly affects the result of subsequent positioning. In addition, when the problem of simultaneous positioning of multiple information sources is solved by the traditional two-step positioning, an additional information matching step is needed, and the practical application is not facilitated. The direct positioning technology directly extracts the position information from the original data layer without estimating intermediate parameters, effectively avoids the loss of useful information, and realizes the simultaneous positioning of multiple information sources while improving the positioning precision. However, because of the limitation of the degree of freedom of the array antenna, the existing direct positioning technology can only realize the simultaneous positioning of multiple information sources with the information source number smaller than the array element number. Therefore, how to break through the limitation of the degree of freedom of the array antenna while ensuring the positioning accuracy is a key problem.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a multi-information-source direct positioning method based on an unmanned aerial vehicle loading nested array, and by organically combining the advantages of an array antenna with a high-precision direct positioning technology, the problems that the positioning precision of the traditional two-step positioning method is limited and an additional information matching step is relied on are solved, and the problem that the existing direct positioning technology cannot realize the simultaneous positioning of multiple information sources when the number of the information sources exceeds the number of array elements is solved, and the multi-information-source precise positioning can be completed only by one unmanned aerial vehicle, so that the method has important engineering application value.
The invention provides the following technical scheme for achieving the aim:
the utility model provides a multi-source direct positioning method based on unmanned aerial vehicle loading nested array, its basic thinking is: the unmanned aerial vehicle receives a plurality of radiation source signals at L different positions and samples the received signals; respectively calculating a received signal sampling covariance matrix of each position, and carrying out vectorization processing on the received signal sampling covariance matrix; fusing the L vectorized observation signals to obtain vectorized virtual receiving signals; and constructing a loss function of the position estimation by adopting a direct correlation method, and obtaining a final radiation source position estimation result through grid search.
The invention is characterized by comprising the following steps:
step 1: the unmanned aerial vehicle receives a plurality of radiation source signals in L different positions, and samples the received signal:
suppose that the K source positions are respectively pk＝[xk,yk]TThe unmanned aerial vehicle mounts a nested array with M elements, wherein M is N1+N2，N1And N2The number of the array elements of the two uniform linear arrays is respectively. The number of observation positions of the unmanned aerial vehicle is L, and the coordinates of the observation positions are respectively
Then the receiving signal of the unmanned plane at the l position is
Wherein,
is the power fading coefficient, λ is the wavelength, β is the path loss factor,
dmindicating the position of the mth array element relative to the reference array element under the nested array pattern,
sl,kand (t) is a transmission signal of a kth source.
Step 2: respectively calculating a received signal sampling covariance matrix of each position, and carrying out vectorization treatment on the received signal sampling covariance matrix:
because the actual signal sampling length is limited, the signal covariance matrix is replaced by the sampling covariance matrix and is calculated as
Wherein J is the number of fast beats. Vectorization processing is carried out on the covariance matrix of the received signal samples at the ith position to obtain
Wherein,
a power vector representing the power component of the received signal,
is the noise power.
And step 3: fusing the L vectorized observation signals to obtain vectorized virtual receiving signals:
memory vector
A power vector formed by the power of the transmitted signal is obtained
Note the book
The virtual received signal of the ith observation position can be represented as
The virtual received signals of all L positions are fused to obtain the virtual received signals of L positions as
Wherein,
and 4, step 4: constructing a loss function of position estimation by adopting a direct correlation method, and obtaining a final radiation source position estimation result by grid search:
constructing a loss function according to the virtual received signal in step 3
Wherein, wl(p)＝||p-ulThe | | is a balance factor,
and searching the loss function to obtain coordinates corresponding to the first K peak values, namely the radiation source position estimation result.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
the secondary loss of the position information is avoided, and the positioning precision is effectively improved;
the simultaneous positioning of multiple information sources can be realized without additional information matching;
and thirdly, the limitation of the degree of freedom of the array antenna is broken through, and the simultaneous positioning of multiple information sources when the number of the information sources is greater than the number of the array elements is realized.
Drawings
Fig. 1 is a flowchart of a multi-source direct positioning method based on an unmanned aerial vehicle-mounted nested array provided by the invention.
Fig. 2 is a multi-source positioning scene graph based on the unmanned aerial vehicle according to the present invention.
Fig. 3 is a comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method under different noise powers when the number of signal sources is less than the number of array elements.
Fig. 4 shows the comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method at different snapshots when the number of the information sources is less than the number of the array elements.
Fig. 5 is a comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method under different noise powers when the number of the source is greater than the number of the array elements.
Fig. 6 shows the comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method at different snapshots when the number of the source is greater than the number of the array elements.
Fig. 7 is a comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method at different snapshots when the number of the source is greater than the number of the array elements.
Detailed Description
The technical scheme of the invention is further described in detail by combining the drawings and the specific embodiments:
the detailed flow of the multi-information-source direct positioning method based on the unmanned aerial vehicle loading nested array is shown in fig. 1, wherein the unmanned aerial vehicle receives a plurality of radiation source signals at L different positions and samples the received signals; respectively calculating a received signal sampling covariance matrix of each position, and carrying out vectorization processing on the received signal sampling covariance matrix; fusing the L vectorized observation signals to obtain vectorized virtual receiving signals; and constructing a loss function of the position estimation by adopting a direct correlation method, and obtaining a final radiation source position estimation result through grid search. The concrete implementation is as follows:
step 1: the unmanned aerial vehicle receives a plurality of radiation source signals in L different positions, and samples the received signal:
suppose that the K source positions are respectively pk＝[xk,yk]TThe unmanned aerial vehicle mounts a nested array with M elements, wherein M is N1+N2，N1And N2The number of the array elements of the two uniform linear arrays is respectively. The number of observation positions of the unmanned aerial vehicle is L, and the coordinates of the observation positions are respectively
Then the receiving signal of the unmanned plane at the l position is
Wherein,
is the power fading coefficient, λ is the wavelength, β is the path loss factor,
dmindicating the position of the mth array element relative to the reference array element under the nested array pattern,
sl,kand (t) is a transmission signal of a kth source.
Step 2: respectively calculating a received signal sampling covariance matrix of each position, and carrying out vectorization treatment on the received signal sampling covariance matrix:
because the actual signal sampling length is limited, the signal covariance matrix is replaced by the sampling covariance matrix and is calculated as
Wherein J is the number of fast beats. Vectorization processing is carried out on the covariance matrix of the received signal samples at the ith position to obtain
Wherein,
a power vector representing the power component of the received signal,
is the noise power.
And step 3: fusing the L vectorized observation signals to obtain vectorized virtual receiving signals:
memory vector
A power vector formed by the power of the transmitted signal is obtained
Note the book
The virtual received signal of the ith observation position can be represented as
The virtual received signals of all L positions are fused to obtain the virtual received signals of L positions as
Wherein,
and 4, step 4: constructing a loss function of position estimation by adopting a direct correlation method, and obtaining a final radiation source position estimation result by grid search:
constructing a loss function according to the virtual received signal in step 3
Wherein, wl(p)＝||p-ulThe | | is a balance factor,
and searching the loss function to obtain coordinates corresponding to the first K peak values, namely the radiation source position estimation result.
FIG. 3 is a scattergram of the radiation source position estimation of the method of the present invention at a noise power of 0.8-watt, the number of elements of the nested array is 6, and the number of fast beats is 100. The signal power of the radiation source is 100-watt, the number of the radiation sources is 7, and the positions are respectively (400,200), (200,700), (600,400), (400,900), (300,500), (500,700) and (200,300), and the unit is m. The initial position of the unmanned aerial vehicle is used as the original point, the unmanned aerial vehicle continuously flies 10 observation points along the x axis, the flying speed is 20m/s, and the observation is carried out once every 5s of flying. As can be seen from the figure, the invention can effectively realize the simultaneous positioning of a plurality of radiation sources when the number of the information sources is greater than that of the array elements.
Fig. 4 is a comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method under different noise powers when the number of signal sources is less than the number of array elements. The simulation parameters are set as follows: the number of radiation sources is 3, and the positions are (400,200), (200,700) and (900,400) respectively, and the unit is m; the unmanned aerial vehicle carries a nested array with the array element number of 6, the unmanned aerial vehicle continuously flies 10 observation points along the x axis by taking the initial position of the unmanned aerial vehicle as an original point, the flying speed is 20m/s, and the observation is carried out once every 5 s; the number of fast beats is 100 and the noise power setting is shown in figure 4. It can be seen from the figure that when the number of the information sources is less than the number of the array elements, the positioning error of the method is reduced along with the reduction of the noise power, and the positioning error of the method is always lower than that of the traditional positioning method, so that the performance is obviously improved.
Fig. 5 shows the comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method at different snapshots when the number of the source is less than the number of the array elements. The simulation parameters are set as follows: the number of radiation sources is 3, the positions are (400,200), (200,700) and (900,400), the unit is m, and the source signal power is 50-watt; the unmanned aerial vehicle carries a nested array with the array element number of 6, the unmanned aerial vehicle continuously flies 10 observation points along the x axis by taking the initial position of the unmanned aerial vehicle as an original point, the flying speed is 20m/s, and the observation is carried out once every 5 s; the fast beat number setting is shown in fig. 5. It can be seen from the figure that when the number of the information sources is less than the number of the array elements, the positioning accuracy of the two methods is reduced along with the increase of the fast beat number, and the method disclosed by the invention always has lower positioning error.
Fig. 6 is a comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method under different noise powers when the number of the source is greater than the number of the array elements. The simulation parameters are set as follows: the number of radiation sources is 7, the positions are respectively (400,200), (200,700), (600,400), (400,900), (300,500), (500,700), (200,300), the unit is m, the power of the source signal is 80-watt; the unmanned aerial vehicle carries a nested array with the array element number of 6, the unmanned aerial vehicle continuously flies 10 observation points along the x axis by taking the initial position of the unmanned aerial vehicle as an original point, the flying speed is 20m/s, and the observation is carried out once every 5 s; the number of fast beats is 100 and the noise power setting is shown in figure 6. It can be seen from the figure that when the number of the information sources is greater than the number of the array elements, the method still has higher positioning accuracy under the condition of higher noise power, and compared with the traditional two-step positioning method, the method provided by the invention has the advantage that the positioning accuracy is obviously improved.
Fig. 7 is a comparison of the positioning performance of the method of the present invention and the conventional two-step positioning method at different snapshots when the number of the source is greater than the number of the array elements. The simulation parameters are set as follows: the number of radiation sources is 7, the positions are respectively (400,200), (200,700), (600,400), (400,900), (300,500), (500,700), (200,300), the unit is m, the power of the source signal is 50-watt; the unmanned aerial vehicle carries a nested array with the array element number of 6, the unmanned aerial vehicle continuously flies 10 observation points along the x axis by taking the initial position of the unmanned aerial vehicle as an original point, the flying speed is 20m/s, and the observation is carried out once every 5 s; the fast beat number setting is shown in fig. 7. As can be seen from the figure, when the number of the information sources is greater than the number of the array elements, the method still has higher positioning accuracy under the condition of small snapshot number, and compared with the traditional two-step positioning method, the method provided by the invention has the advantage that the positioning accuracy is obviously improved.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can understand that the modifications or substitutions within the technical scope of the present invention are included in the scope of the present invention, and therefore, the scope of the present invention should be subject to the protection scope of the claims.
Claims (1)
1. A multi-information-source direct positioning method based on an unmanned aerial vehicle loaded nested array is characterized by comprising the following steps:
step 1: the unmanned aerial vehicle receives a plurality of radiation source signals in L different positions, and samples the received signal:
let K information source positions be p respectivelyk＝[xk,yk]TThe unmanned aerial vehicle mounts a nested array with M elements, wherein M is N1+N2，N1And N2The number of the array elements of the two uniform linear arrays is respectively; the number of observation positions of the unmanned aerial vehicle is L, and the coordinates of the observation positions are respectively
Then the receiving signal of the unmanned plane at the l position is
Wherein,
is the power fading coefficient, λ is the wavelength, β is the path loss factor,
dmindicating the position of the mth array element relative to the reference array element under the nested array pattern,
sl,k(t) is a transmission signal of a kth source;
step 2: respectively calculating a received signal sampling covariance matrix of each position, and carrying out vectorization treatment on the received signal sampling covariance matrix:
due to the finite length of the actual signal samples, the signal covariance matrix is replaced by the sampling covariance matrix as follows:
wherein J is the number of fast beats; vectorization processing is carried out on the covariance matrix of the received signal samples at the ith position to obtain
Wherein,
a power vector representing the power component of the received signal,
is the noise power;
and step 3: fusing the L vectorized observation signals to obtain vectorized virtual receiving signals:
memory vector
A power vector formed by the power of the transmitted signal is obtained
Note the book
The virtual received signal of the ith observation position can be represented as
The virtual received signals of all L positions are fused to obtain the virtual received signals of L positions as
Wherein,
and 4, step 4: constructing a loss function of position estimation by adopting a direct correlation method, and obtaining a final radiation source position estimation result by grid search:
constructing a loss function according to the virtual received signal in step 3
Wherein, wl(p)＝||p-ulThe | | is a balance factor,
and searching the loss function to obtain coordinates corresponding to the first K peak values, namely the radiation source position estimation result.
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Application publication date: 20210126 |