CN114578313A - Centroid search-based grid detection mirror image elimination method and device - Google Patents
Centroid search-based grid detection mirror image elimination method and device Download PDFInfo
- Publication number
- CN114578313A CN114578313A CN202210495957.2A CN202210495957A CN114578313A CN 114578313 A CN114578313 A CN 114578313A CN 202210495957 A CN202210495957 A CN 202210495957A CN 114578313 A CN114578313 A CN 114578313A
- Authority
- CN
- China
- Prior art keywords
- grid
- signal
- target
- threshold
- noise ratio
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M1/00—Testing static or dynamic balance of machines or structures
- G01M1/12—Static balancing; Determining position of centre of gravity
- G01M1/122—Determining position of centre of gravity
Abstract
The invention relates to the field of radar signal joint detection, and provides a grid detection mirror image elimination method and device based on centroid search, wherein the method comprises the following steps: registering each channel radar signal to each space grid; calculating the signal-to-noise ratio and the sum of the signal-to-noise ratios of all channels of all grids; screening out a target grid array meeting preset requirements; sorting elements in the target grid array in a descending order according to the sum of the signal-to-noise ratios; selecting all grids with the maximum sum of signal-to-noise ratios and calculating the centroids of the grids; storing the grids closest to the centroid into a target set, updating echo data of each channel and deleting the grids from a target grid array; calculating the sum of the signal-to-noise ratio and the signal-to-noise ratio of each channel of each grid in the target grid array; screening target grids meeting preset requirements; and judging whether the target grids exist or not, if so, returning to the step of sorting, and otherwise, taking the information contained in the target set as real target information. The method and the device can improve the accuracy of image elimination and the grid detection precision, and reduce the number of grids so as to reduce the operation amount.
Description
Technical Field
The disclosure relates to the technical field of radar signal joint detection, in particular to a grid detection mirror image elimination method and device based on centroid searching.
Background
The rasterization joint detection is a radar multi-channel signal fusion detection method, which divides a space into a plurality of grid areas, matches each channel echo signal distance unit to each space grid according to the relative radar position of each grid area and the signal two-way delay condition, completes signal registration fusion, and further detects a target according to each grid fusion signal, thereby completing joint detection.
For a mirror image target and a real target with the same Signal-to-Noise Ratio (SNR) value, the existing grid detection mirror image elimination method usually selects the stored first target as the real target, however, the method cannot identify the mirror image target and the real target with the same SNR value, so that the mirror image elimination is inaccurate, and the detection performance is reduced. In addition, in the prior art, in order to improve the grid detection precision, a small-size grid is usually selected for detection, however, since the smaller the grid size in the same space is, the more the number of grids is, the smaller the grid size is, the larger the calculation amount is, and the detection performance is reduced.
Disclosure of Invention
The present disclosure is directed to at least one of the problems in the prior art, and provides a method and an apparatus for eliminating a grid detection mirror image based on centroid finding.
In one aspect of the present disclosure, a method for eliminating a grid detection mirror image based on centroid finding is provided, including:
step S110: registering the radar signals of each channel to each space grid to obtain a corresponding initial grid array;
step S120: calculating the signal-to-noise ratio of each channel corresponding to each grid in the initial grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid;
step S130: screening grids meeting preset requirements from the initial grid array according to a preset single grid signal-to-noise ratio threshold, a single channel signal-to-noise ratio threshold and a channel number threshold to obtain a corresponding target grid array; the preset requirements comprise that the sum of signal-to-noise ratios is larger than or equal to a single-grid signal-to-noise ratio threshold, and the number of channels with the signal-to-noise ratios larger than or equal to a single-channel signal-to-noise ratio threshold is larger than or equal to a channel number threshold;
step S140: sorting the elements in the target grid array in a descending order according to the sum of the signal-to-noise ratios of all channels corresponding to each grid;
step S150: selecting all grids which are the same as the sum of signal-to-noise ratios of the first elements in the sorted target grid array from the initial grid array to form an intermediate grid array, and calculating the mass center of each element in the intermediate grid array;
step S160: taking a grid which is closest to the centroid in the middle grid array as a representative grid of the middle grid array, storing the representative grid into a target set, clearing echo data corresponding to radar signals of all channels corresponding to the representative grid, updating the echo data of all channels, and deleting the representative grid from the target grid array;
step S170: calculating the signal-to-noise ratio of each channel corresponding to each grid in the target grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid according to the updated echo data of each channel;
step S180: according to the single-grid signal-to-noise ratio threshold, the single-channel signal-to-noise ratio threshold and the channel number threshold, selecting grids meeting preset requirements from the target grid array as target grids;
step S190: and judging whether the target grid exists, if so, returning to the step S140, and if not, taking the information contained in the target set as real target information.
Optionally, step S130 includes:
comparing the sum of the signal-to-noise ratios corresponding to each grid in the initial grid array with a single grid signal-to-noise ratio threshold, and comparing the number of threshold-passing channels corresponding to each grid with a channel number threshold, wherein the number of threshold-passing channels corresponding to each grid is used for indicating the number of channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single channel signal-to-noise ratio threshold;
and selecting grids with the sum of the signal-to-noise ratios being greater than or equal to the single-grid signal-to-noise ratio threshold and the number of channels exceeding the threshold being greater than or equal to the channel number threshold from the initial grid array to form a target grid array.
Optionally, comparing the number of channels passing the threshold corresponding to each grid with the threshold of the number of channels includes:
comparing the signal-to-noise ratio of each channel corresponding to each grid in the initial grid array with a single-channel signal-to-noise ratio threshold, and counting the number of channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold to obtain the number of threshold-passing channels corresponding to each grid;
and comparing the number of the threshold-passing channels corresponding to each grid with a channel number threshold value.
Alternatively, the centroid is represented as
Wherein, in the step (A),
is the centroid longitude and
，
is the centroid latitude
，
Is the height of the center of mass
，iIs the grid number, M is the number of grids in the middle grid array,
is a gridiThe center longitude of (a) is determined,
is a gridiThe central latitude of (a) is,
is a gridiThe center height of (a).
Optionally, the distance of the centroid from the grid
Is shown as
。
Optionally, step S180 includes:
comparing the signal-to-noise ratio of each channel corresponding to each grid in the target grid array with a single-channel signal-to-noise ratio threshold respectively, and counting the number of channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold to obtain the number of threshold-passing channels corresponding to each grid;
comparing the sum of the signal-to-noise ratios corresponding to each grid in the target grid array with a single grid signal-to-noise ratio threshold, and comparing the number of threshold-passing channels corresponding to each grid with a channel number threshold;
and selecting the grids with the signal-to-noise ratio sum being greater than or equal to the single-grid signal-to-noise ratio threshold and the threshold-crossing channel number being greater than or equal to the channel number threshold from the target grid array as target grids.
Optionally, step S110 includes:
acquiring echo data corresponding to the radar signals of each channel to obtain a corresponding echo array;
dividing the common visual area space into a plurality of three-dimensional space grids according to preset longitude intervals, latitude intervals and altitude intervals;
and respectively calculating distance units in the echo array corresponding to each three-dimensional space grid according to the azimuth angle, the pitch angle and the distance of each three-dimensional space grid and each radar node, and completing registration of the radar signal of each channel and the three-dimensional space grid to obtain an initial grid array.
In another aspect of the present disclosure, there is provided a centroid-finding based grid detection mirror image elimination apparatus, including:
the registration module is used for registering the radar signals of all channels to all space grids to obtain corresponding initial grid arrays;
the first calculation module is used for calculating the signal-to-noise ratio of each channel corresponding to each grid in the initial grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid;
the first screening module is used for screening grids meeting preset requirements from the initial grid array according to a preset single-grid signal-to-noise ratio threshold, a single-channel signal-to-noise ratio threshold and a channel number threshold to obtain a corresponding target grid array; the preset requirements comprise that the sum of signal-to-noise ratios is more than or equal to a single-grid signal-to-noise ratio threshold, and the number of channels with the signal-to-noise ratios more than or equal to a single-channel signal-to-noise ratio threshold is more than or equal to a channel number threshold;
the sorting module is used for sorting the elements in the target grid array in a descending order according to the sum of the signal-to-noise ratios of all channels corresponding to each grid;
the selecting module is used for selecting all grids which are the same as the sum of signal-to-noise ratios of the first elements in the sorted target grid array from the initial grid array to form an intermediate grid array, and calculating the mass center of each element in the intermediate grid array;
the updating module is used for storing a grid which is closest to the centroid in the middle grid array as a representative grid of the middle grid array into a target set, clearing echo data corresponding to radar signals of all channels corresponding to the representative grid, updating the echo data of all channels, and deleting the representative grid from the target grid array;
the second calculation module is used for calculating the signal-to-noise ratio of each channel corresponding to each grid in the target grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid according to the updated echo data of each channel;
the second screening module is used for screening grids meeting preset requirements from the target grid array as target grids according to the single-grid signal-to-noise ratio threshold, the single-channel signal-to-noise ratio threshold and the channel number threshold;
and the judging module is used for judging whether the target grid exists or not, if so, the sorting module is triggered, and if not, the information contained in the target set is used as the real target information.
In another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the centroid lookup based grid detect image elimination method described above.
In another aspect of the present disclosure, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the method for grid detection image elimination based on centroid finding as described above is implemented.
Compared with the prior art, the method has the advantages that the distribution of the real target and the mirror image target with the same signal-to-noise ratio is counted, the distribution center of mass is calculated to estimate the position of the real target, the mirror image target is screened, the accuracy of mirror image elimination and the grid detection precision are improved, and meanwhile, the center of mass is adopted to estimate the position of the real target and distinguish the mirror image target, so that a large-size grid is adopted to obtain higher detection performance during grid detection, the number of the grids is reduced, and the problem of increased operation amount caused by more grids is solved.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
Fig. 1 is a flowchart of a method for removing a grid detection mirror image based on centroid finding according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a grid detection mirror image elimination apparatus based on centroid finding according to another embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device according to another embodiment of the present disclosure.
Detailed Description
In the prior art, because the positions and the viewing angles of the radar nodes are different, the shapes of the space units are usually not only complicated but also irregular, so that the grid units can only approximate the space units. However, in the process of signal space-time registration, the target signal may be simultaneously registered to multiple grids near the real position of the target, forming multiple mirror targets with the same signal-to-noise ratio as the real target, and thus the real target and the mirror targets need to be further identified to improve the detection performance. For this reason, the grid detection mirror image elimination method in the prior art generally takes the first grid stored in sequence as a real target, and the grid detection mirror image elimination method includes the following steps:
step S0: registering each channel radar signal to each spatial grid.
Step S1: and (4) counting the SNR value of each channel of each grid and the sum of the SNR of all the channels to prepare for screening the grid with the target.
Step S2: and screening the target grids meeting the requirements according to the preset SNR threshold and the threshold of the number of channels passing the SNR threshold.
Step S3: the satisfactory target grids are sorted by SNR and descending order.
Step S4: and storing the first grid information to a target set according to a storage sequence, clearing radar echo values of all channels corresponding to the grids, and eliminating the grid information from the target grids.
Step S5: and re-counting the sum of the SNR value of each target grid and the SNR values of all channels.
Step S6: repeating the steps S2 to S4 until there is no more qualified target grid.
Step S7: at this time, the grid information stored in the target set is the real target information.
Since the grid detection mirror image elimination method in the prior art uses the first grid stored in sequence as the real target, the prior art cannot identify the mirror image target and the real target with the same SNR value, and the mirror image elimination is not accurate, which may result in the reduction of the detection performance.
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that in various embodiments of the disclosure, numerous technical details are set forth in order to provide a better understanding of the disclosure. However, the technical solution claimed in the present disclosure can be implemented without these technical details and various changes and modifications based on the following embodiments. The following embodiments are divided for convenience of description, and no limitation should be made to specific implementations of the present disclosure, and the embodiments may be mutually incorporated and referred to without contradiction.
One embodiment of the present disclosure relates to a grid detection mirror image elimination method based on centroid search, including:
step S110: and registering the radar signals of all channels to all space grids to obtain corresponding initial grid arrays.
Illustratively, step S110 includes:
acquiring echo data corresponding to the radar signals of each channel to obtain a corresponding echo array; dividing the common visual area space into a plurality of three-dimensional space grids according to preset longitude intervals, latitude intervals and height intervals; and respectively calculating distance units in the echo array corresponding to each three-dimensional space grid according to the azimuth angle, the pitch angle and the distance of each three-dimensional space grid and each radar node, and completing registration of the radar signal of each channel and the three-dimensional space grid to obtain an initial grid array.
The common visual area space is divided into a plurality of three-dimensional space grids according to the preset longitude interval, the preset latitude interval and the preset altitude interval, and the registration of the radar signals of all channels and the three-dimensional space grids is completed on the basis, so that the problem of increased operation amount caused by the detection by adopting small-size grids can be avoided, and the detection performance is improved.
Step S120: and calculating the signal-to-noise ratio of each channel corresponding to each grid in the initial grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid.
Step S130: screening grids meeting preset requirements from the initial grid array according to a preset single grid signal-to-noise ratio threshold, a single channel signal-to-noise ratio threshold and a channel number threshold to obtain a corresponding target grid array; the preset requirements comprise that the sum of signal-to-noise ratios is larger than or equal to a single-grid signal-to-noise ratio threshold, and the number of channels with the signal-to-noise ratios larger than or equal to a single-channel signal-to-noise ratio threshold is larger than or equal to a channel number threshold.
Illustratively, step S130 includes:
comparing the sum of the signal-to-noise ratios corresponding to each grid in the initial grid array with a single grid signal-to-noise ratio threshold, and comparing the number of threshold-passing channels corresponding to each grid with a channel number threshold, wherein the number of the threshold-passing channels corresponding to each grid is used for indicating the number of the channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single channel signal-to-noise ratio threshold; and selecting grids with the sum of the signal-to-noise ratios being greater than or equal to the single-grid signal-to-noise ratio threshold and the number of channels exceeding the threshold being greater than or equal to the channel number threshold from the initial grid array to form a target grid array.
Illustratively, comparing the number of channels that pass the threshold value with respect to each grid includes:
comparing the signal-to-noise ratio of each channel corresponding to each grid in the initial grid array with a single-channel signal-to-noise ratio threshold, and counting the number of channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold to obtain the number of threshold-passing channels corresponding to each grid; and comparing the number of the threshold-passing channels corresponding to each grid with a channel number threshold value.
Step S140: and sorting the elements in the target grid array in a descending order according to the sum of the signal-to-noise ratios of all channels corresponding to each grid.
Step S150: and selecting all grids which are the same as the sum of signal-to-noise ratios of the first elements in the sorted target grid array from the initial grid array to form an intermediate grid array, and calculating the mass center of each element in the intermediate grid array.
Illustratively, the centroid is represented as
Wherein, in the step (A),
is the centroid longitude and
，
is the centroid latitude
，
Is the height of the center of mass
，iIs the grid number, M is the number of grids in the middle grid array,
is a gridiThe center longitude of (a) is determined,
is a gridiThe central latitude of (a) is,
is a gridiThe center height of (a).
Step S160: and taking the grid closest to the centroid in the middle grid array as a representative grid of the middle grid array to be stored in a target set, clearing echo data corresponding to the radar signals of all channels corresponding to the representative grid, updating the echo data of all channels, and deleting the representative grid from the target grid array.
Illustratively, the distance of the centroid from the grid
Is shown as
。
Step S170: and calculating the signal-to-noise ratio of each channel corresponding to each grid in the target grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid according to the updated echo data of each channel.
Step S180: and screening grids meeting preset requirements from the target grid array as target grids according to the single grid signal-to-noise ratio threshold, the single channel signal-to-noise ratio threshold and the channel number threshold. The preset requirement in this step is the same as the preset requirement in step S130.
Illustratively, step S180 includes:
comparing the signal-to-noise ratio of each channel corresponding to each grid in the target grid array with a single-channel signal-to-noise ratio threshold respectively, and counting the number of channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold to obtain the number of threshold-passing channels corresponding to each grid; comparing the sum of the signal-to-noise ratios corresponding to each grid in the target grid array with a single grid signal-to-noise ratio threshold, and comparing the number of threshold-passing channels corresponding to each grid with a channel number threshold; and selecting the grids with the sum of the signal-to-noise ratios being greater than or equal to the single-grid signal-to-noise ratio threshold and the number of channels exceeding the threshold being greater than or equal to the channel number threshold from the target grid array as target grids.
Step S190: and judging whether the target grid exists, if so, returning to the step S140, and if not, taking the information contained in the target set as real target information.
Compared with the prior art, the method and the device have the advantages that the distribution of the real target and the mirror image target with the same signal-to-noise ratio is counted, the distribution center of mass is calculated to estimate the position of the real target, the mirror image target is screened, the accuracy of mirror image elimination and the grid detection precision are improved, and meanwhile, the center of mass is adopted to estimate the position of the real target and distinguish the mirror image target, so that when grid detection is carried out, a large-size grid is adopted to obtain high detection performance, the number of grids is reduced, and the problem that the number of operation is increased due to the fact that the number of the grids is large is solved.
In order to make the above embodiments better understood by those skilled in the art, a specific example is described below.
As shown in fig. 1, a method for eliminating grid detection mirror image based on centroid search includes the following steps:
step S00: registering each channel radar signal to each spatial grid: reading the echo data corresponding to the radar signal of each channel, and storing the echo data into a corresponding echo array
And (4) array. According to a preset longitude interval
Interval of latitude
Height interval of
Dividing the common visual area space into a plurality of three-dimensional space grids, and according to the azimuth angle corresponding to each radar node and each three-dimensional space grid
And a pitch angle
And distance
Separately computing the data corresponding to each three-dimensional space grid
And the distance units in the array complete the registration of the radar signals of all channels and the three-dimensional space grid to obtain an initial grid array.
Step S01: and counting the SNR values of each grid, each channel and the sum of the SNR values of all the channels: respectively calculating SNR values of channels corresponding to grids in the initial grid array according to the signal registration result
Wherein, in the step (A),
，ithe number of the grids is given by the numbers,
is a channel number, N is a positive integer,
in order to be the amplitude of the signal,
is the noise amplitude. According to the SNR value of each channel corresponding to each grid, calculating the sum of the SNR values of all channels corresponding to each grid
Wherein, in the process,
。
step S02: screening a target grid meeting the requirement according to a preset SNR threshold and a threshold of the number of channels passing the SNR threshold: according to the preset signal-to-noise ratio threshold of the single grid
Single channel signal-to-noise ratio threshold
And channel number threshold
And screening a target grid meeting the preset requirement from the initial grid array, wherein the method comprises the following steps:
(1) respectively comparing SNR values of channels corresponding to grids in the initial grid array with a preset single-channel signal-to-noise ratio threshold
Comparing, and counting the number of threshold-crossing channels corresponding to each grid
That is, the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold
The number of channels of (a);
(2) summing SNR values of all channels corresponding to each grid in the initial grid array
And a preset single grid signal-to-noise ratio threshold
Carrying out comparison;
(3) the number of the threshold-crossing channels corresponding to each grid in the initial grid array
And a preset channel number threshold
Comparing;
(4) selecting the initial grid array
And is
The grid of (2) constituting a target grid array
Wherein the target grid array
Can be expressed as
，
Is a gridiThe center longitude of (a) is determined,
is a gridiThe central latitude of (a) is,
is a gridiThe center height of (a).
Step S03: sorting the selected target grids meeting the requirements in descending order according to SNR and value: according to each grid
Value, to target grid array
The elements in (1) are sorted in descending order.
Step S04:selecting all grids with the maximum SNR sum value, and counting the centroid positions: selecting grids with the same signal-to-noise ratio sum as the first element in the sorted target grid array from the initial grid array to form an intermediate grid array, and calculating the centroid of each element in the intermediate grid array
Wherein, in the step (A),
is the centroid longitude and
，
is the centroid latitude
，
Is the height of the center of mass
And M is the number of grids in the middle grid array.
Step S05: selecting a grid closest to the centroid, storing the grid to a target set, resetting the radar echo value of each channel corresponding to the grid, and clearing the grid information from the target grid: selecting the distance centroid in the middle grid array
The nearest grid is taken as the representative grid of the intermediate grid array, where the distance of the centroid from the grid
Is shown as
. Storing a representative grid into a target set
An array of data sets, wherein,
the array can be represented as
，
First in an arrayoAn element
Can be expressed as
，
Is composed of
First in an arrayoThe center longitude of the grid to which the individual element corresponds,
is composed of
First in the arrayoThe central latitude of the grid corresponding to each element,
is composed of
First in an arrayoThe center height of the grid corresponding to each element,
is composed of
First in an arrayoThe sum of the SNR values corresponding to the grids corresponding to the elements,
is composed of
First in an arrayoThe SNR value of each channel corresponding to the grid corresponding to each element,
is composed of
The number of elements in the array. The echo array corresponding to the representative grid is
Clearing the echo data in the array, namely clearing the echo data corresponding to the radar signals of each channel corresponding to the representative grid, updating the echo data of each channel, and performing the echo data clearing from the target grid array
The representative grid is deleted.
Step S06: and re-counting the sum of the SNR value of each target grid and the SNR values of all channels: according to updated
Echo data in array, calculating target grid array
Of channels corresponding to grids
Value, and what each grid corresponds toSum of SNR values of channels
。
Step S07: screening a target grid meeting the requirement according to a preset SNR threshold and a threshold of the number of channels passing the SNR threshold: according to the preset signal-to-noise ratio threshold of the single grid
Single channel signal-to-noise ratio threshold
And channel number threshold
From the target grid array
The medium screening of the grids meeting the preset requirements comprises the following steps:
(1) grid array of targets
The SNR value of each channel corresponding to each grid is respectively compared with the preset single-channel SNR threshold
Comparing, and counting the number of threshold-crossing channels corresponding to each grid
That is, the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold
The number of channels of (a);
(2) array of target grids
All channels corresponding to each gridSum of SNR values of
And a preset single grid signal-to-noise ratio threshold
Comparing;
(3) grid array of targets
The number of the passage passing the threshold corresponding to each grid
And a preset channel number threshold
Comparing;
(4) selecting a target grid array
In
And is
As a target grid.
Step S08: judging whether a target grid exists, if so, executing a step S03; if not, step S09 is executed.
Step S09: the grid information in the target set is the real target information: aggregating the targets
And taking the grid position and other information contained in the array as the estimated real target information, and finishing the suppression of the false target.
Another embodiment of the present disclosure relates to a centroid finding based grid detection mirror image elimination apparatus, as shown in fig. 2, including:
a registration module 201, configured to register the radar signals of each channel to each spatial grid, so as to obtain a corresponding initial grid array;
a first calculating module 202, configured to calculate a signal-to-noise ratio of each channel corresponding to each grid in the initial grid array, and a sum of the signal-to-noise ratios of all channels corresponding to each grid;
the first screening module 203 is configured to screen out a grid meeting preset requirements from the initial grid array according to a preset single-grid signal-to-noise ratio threshold, a single-channel signal-to-noise ratio threshold and a channel number threshold, so as to obtain a corresponding target grid array; the preset requirements comprise that the sum of signal-to-noise ratios is more than or equal to a single-grid signal-to-noise ratio threshold, and the number of channels with the signal-to-noise ratios more than or equal to a single-channel signal-to-noise ratio threshold is more than or equal to a channel number threshold;
the sorting module 204 is configured to sort the elements in the target grid array in a descending order according to the sum of the signal-to-noise ratios of all channels corresponding to each grid;
a selecting module 205, configured to select all grids from the initial grid array that have the same sum of signal-to-noise ratios as the first element in the sorted target grid array, to form an intermediate grid array, and calculate a centroid of each element in the intermediate grid array;
an update module 206, configured to store a grid closest to the centroid in the intermediate grid array as a representative grid of the intermediate grid array in the target set, zero-clear the radar signal of each channel corresponding to the representative grid in the initial grid array, update the initial grid array, and delete the representative grid from the target grid array;
a second calculating module 207, configured to calculate, according to the updated initial grid array, a signal-to-noise ratio of each channel corresponding to each grid in the target grid array, and a sum of the signal-to-noise ratios of all channels corresponding to each grid;
the second screening module 208 is configured to screen a grid meeting a preset requirement from the target grid array as a target grid according to the single-grid signal-to-noise ratio threshold, the single-channel signal-to-noise ratio threshold, and the channel number threshold;
the determining module 209 is configured to determine whether a target grid exists, trigger the sorting module 204 if the target grid exists, and take information included in the target set as real target information if the target grid does not exist.
The specific implementation method of the device for eliminating the grid detection mirror image based on centroid finding provided by the embodiment of the present disclosure may be referred to the method for eliminating the grid detection mirror image based on centroid finding provided by the embodiment of the present disclosure, and is not described herein again.
Compared with the prior art, the method and the device have the advantages that the distribution of the real target and the mirror image target with the same signal-to-noise ratio is counted, the distribution center of mass is calculated to estimate the position of the real target, the mirror image target is screened, the accuracy of mirror image elimination and the grid detection precision are improved, and meanwhile, the center of mass is adopted to estimate the position of the real target and distinguish the mirror image target, so that a large-size grid is adopted to obtain higher detection performance during grid detection, the number of grids is reduced, the problem of increased operation amount caused by the large number of grids is solved, and the detection performance is improved.
Another embodiment of the present disclosure relates to an electronic device, as shown in fig. 3, including:
at least one processor 301; and the number of the first and second groups,
a memory 302 communicatively coupled to the at least one processor 301; wherein, the first and the second end of the pipe are connected with each other,
the memory 302 stores instructions executable by the at least one processor 301 to cause the at least one processor 301 to perform the centroid lookup based grid detection image elimination method as described in the previous embodiments.
Where the memory and processor are connected by a bus, the bus may comprise any number of interconnected buses and bridges, the bus connecting together various circuits of the memory and the processor or processors. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor is transmitted over a wireless medium via an antenna, which further receives the data and transmits the data to the processor.
The processor is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And the memory may be used to store data used by the processor in performing operations.
Another embodiment of the present disclosure relates to a computer-readable storage medium storing a computer program, which when executed by a processor implements the centroid-finding-based grid detection image elimination method according to the above embodiments.
That is, as can be understood by those skilled in the art, all or part of the steps in the method according to the foregoing embodiments may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps in the method according to each embodiment of the present disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific embodiments for practicing the present disclosure, and that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure in practice.
Claims (10)
1. A grid detection mirror image elimination method based on centroid search is characterized by comprising the following steps:
step S110: registering the radar signals of all channels to all space grids to obtain corresponding initial grid arrays;
step S120: calculating the signal-to-noise ratio of each channel corresponding to each grid in the initial grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid;
step S130: screening grids meeting preset requirements from the initial grid array according to a preset single grid signal-to-noise ratio threshold, a single channel signal-to-noise ratio threshold and a channel number threshold to obtain a corresponding target grid array; the preset requirements comprise that the sum of signal-to-noise ratios is greater than or equal to the single-grid signal-to-noise ratio threshold, and the number of channels with the signal-to-noise ratios greater than or equal to the single-channel signal-to-noise ratio threshold is greater than or equal to the channel number threshold;
step S140: sorting the elements in the target grid array in a descending order according to the sum of the signal-to-noise ratios of all channels corresponding to each grid;
step S150: selecting all grids which are the same as the sum of signal-to-noise ratios of the first elements in the sorted target grid array from the initial grid array to form an intermediate grid array, and calculating the mass center of each element in the intermediate grid array;
step S160: taking a grid which is closest to the centroid in the middle grid array as a representative grid of the middle grid array, storing the representative grid into a target set, clearing echo data corresponding to radar signals of all channels corresponding to the representative grid, updating the echo data of all channels, and deleting the representative grid from the target grid array;
step S170: calculating the signal-to-noise ratio of each channel corresponding to each grid in the target grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid according to the updated echo data of each channel;
step S180: according to the single-grid signal-to-noise ratio threshold, the single-channel signal-to-noise ratio threshold and the channel number threshold, selecting grids meeting the preset requirements from the target grid array as target grids;
step S190: and judging whether the target grid exists, if so, returning to the step S140, and if not, taking the information contained in the target set as real target information.
2. The method according to claim 1, wherein the step S130 comprises:
comparing the sum of the signal-to-noise ratios corresponding to each grid in the initial grid array with the single grid signal-to-noise ratio threshold, and comparing the number of threshold-passing channels corresponding to each grid with the channel number threshold, wherein the number of threshold-passing channels corresponding to each grid is used for indicating the number of channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single channel signal-to-noise ratio threshold;
and selecting the grids with the sum of signal-to-noise ratios greater than or equal to the single-grid signal-to-noise ratio threshold and the number of channels with threshold exceeding the threshold value from the initial grid array to form the target grid array.
3. The method of claim 2, wherein comparing the number of over-threshold channels corresponding to each of the grids to the channel number threshold comprises:
comparing the signal-to-noise ratio of each channel corresponding to each grid in the initial grid array with the single-channel signal-to-noise ratio threshold, and counting the number of the channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold to obtain the number of threshold-passing channels corresponding to each grid;
and comparing the number of the threshold-passing channels corresponding to each grid with the threshold value of the number of the channels.
4. The method of claim 1, wherein the centroid is represented as
Wherein, in the process,
is centroid longitude and
，
is the centroid latitude
，
Is the height of the center of mass
，iIs the grid number, M is the number of grids in the intermediate grid array,
is a gridiThe center longitude of (a) is determined,
is a gridiThe central latitude of (a) is,
is a gridiThe center height of (a).
5. The method of claim 4, wherein the centroid is a distance from the grid
Is shown as
。
6. The method according to claim 1, wherein the step S180 comprises:
comparing the signal-to-noise ratio of each channel corresponding to each grid in the target grid array with the single-channel signal-to-noise ratio threshold respectively, and counting the number of the channels of which the signal-to-noise ratio corresponding to each grid is greater than or equal to the single-channel signal-to-noise ratio threshold to obtain the number of threshold-passing channels corresponding to each grid;
comparing the sum of the signal-to-noise ratios corresponding to each grid in the target grid array with the single grid signal-to-noise ratio threshold, and comparing the number of threshold-passing channels corresponding to each grid with the channel number threshold;
and selecting the grid with the sum of signal-to-noise ratios greater than or equal to the single-grid signal-to-noise ratio threshold and the number of channels with threshold exceeding the threshold value from the target grid array as the target grid.
7. The method according to any one of claims 1 to 6, wherein the step S110 comprises:
acquiring echo data corresponding to the radar signals of each channel to obtain a corresponding echo array;
dividing the common visual area space into a plurality of three-dimensional space grids according to preset longitude intervals, latitude intervals and altitude intervals;
and respectively calculating distance units in the echo array corresponding to the three-dimensional space grids according to the azimuth angle, the pitch angle and the distance of each three-dimensional space grid corresponding to each radar node, and completing registration of the radar signals of each channel and the three-dimensional space grids to obtain the initial grid array.
8. A centroid lookup based grid detection mirror image elimination apparatus, comprising:
the registration module is used for registering the radar signals of all channels to all space grids to obtain corresponding initial grid arrays;
a first calculating module, configured to calculate a signal-to-noise ratio of each channel corresponding to each grid in the initial grid array, and a sum of the signal-to-noise ratios of all channels corresponding to each grid;
the first screening module is used for screening grids meeting preset requirements from the initial grid array according to a preset single-grid signal-to-noise ratio threshold, a single-channel signal-to-noise ratio threshold and a channel number threshold to obtain a corresponding target grid array; the preset requirements comprise that the sum of signal-to-noise ratios is greater than or equal to the single-grid signal-to-noise ratio threshold, and the number of channels with the signal-to-noise ratios greater than or equal to the single-channel signal-to-noise ratio threshold is greater than or equal to the channel number threshold;
the sorting module is used for sorting the elements in the target grid array in a descending order according to the sum of the signal-to-noise ratios of all channels corresponding to the grids;
the selecting module is used for selecting all grids which are the same as the sum of signal-to-noise ratios of the first elements in the ordered target grid array from the initial grid array to form an intermediate grid array, and calculating the mass center of each element in the intermediate grid array;
the updating module is used for storing a grid which is closest to the centroid in the middle grid array as a representative grid of the middle grid array into a target set, clearing echo data corresponding to radar signals of all channels corresponding to the representative grid, updating the echo data of all channels, and deleting the representative grid from the target grid array;
the second calculation module is used for calculating the signal-to-noise ratio of each channel corresponding to each grid in the target grid array and the sum of the signal-to-noise ratios of all channels corresponding to each grid according to the updated echo data of each channel;
the second screening module is used for screening grids meeting the preset requirements from the target grid array as target grids according to the single grid signal-to-noise ratio threshold, the single channel signal-to-noise ratio threshold and the channel number threshold;
and the judging module is used for judging whether the target grid exists or not, if so, triggering the sorting module, and if not, taking the information contained in the target set as real target information.
9. An electronic device, comprising:
at least one processor; and (c) a second step of,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the centroid lookup based grid detection image elimination method of any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the centroid-lookup based grid detection image elimination method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210495957.2A CN114578313B (en) | 2022-05-09 | 2022-05-09 | Centroid lookup-based grid detection mirror image elimination method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210495957.2A CN114578313B (en) | 2022-05-09 | 2022-05-09 | Centroid lookup-based grid detection mirror image elimination method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114578313A true CN114578313A (en) | 2022-06-03 |
| CN114578313B CN114578313B (en) | 2022-07-22 |
Family
ID=81768960
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210495957.2A Active CN114578313B (en) | 2022-05-09 | 2022-05-09 | Centroid lookup-based grid detection mirror image elimination method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114578313B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060041375A1 (en) * | 2004-08-19 | 2006-02-23 | Geographic Data Technology, Inc. | Automated georeferencing of digitized map images |
| CN105027190A (en) * | 2013-01-03 | 2015-11-04 | 美达公司 | Extramissive spatial imaging digital eye glass for virtual or augmediated vision |
| CN106441388A (en) * | 2016-10-25 | 2017-02-22 | 长春工业大学 | Fiber bragg grating demodulation method based on K-L conversion |
| CN106937531A (en) * | 2014-06-14 | 2017-07-07 | 奇跃公司 | Method and system for producing virtual and augmented reality |
| CN107015205A (en) * | 2017-03-15 | 2017-08-04 | 电子科技大学 | A kind of false target removing method of distributed MIMO detections of radar |
| CN111210832A (en) * | 2018-11-22 | 2020-05-29 | 广州广晟数码技术有限公司 | Bandwidth extension audio coding and decoding method and device based on spectrum envelope template |
| CN111985322A (en) * | 2020-07-14 | 2020-11-24 | 西安理工大学 | Road environment element sensing method based on laser radar |
-
2022
- 2022-05-09 CN CN202210495957.2A patent/CN114578313B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060041375A1 (en) * | 2004-08-19 | 2006-02-23 | Geographic Data Technology, Inc. | Automated georeferencing of digitized map images |
| CN105027190A (en) * | 2013-01-03 | 2015-11-04 | 美达公司 | Extramissive spatial imaging digital eye glass for virtual or augmediated vision |
| CN106937531A (en) * | 2014-06-14 | 2017-07-07 | 奇跃公司 | Method and system for producing virtual and augmented reality |
| CN106441388A (en) * | 2016-10-25 | 2017-02-22 | 长春工业大学 | Fiber bragg grating demodulation method based on K-L conversion |
| CN107015205A (en) * | 2017-03-15 | 2017-08-04 | 电子科技大学 | A kind of false target removing method of distributed MIMO detections of radar |
| CN111210832A (en) * | 2018-11-22 | 2020-05-29 | 广州广晟数码技术有限公司 | Bandwidth extension audio coding and decoding method and device based on spectrum envelope template |
| CN111985322A (en) * | 2020-07-14 | 2020-11-24 | 西安理工大学 | Road environment element sensing method based on laser radar |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114578313B (en) | 2022-07-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110443786B (en) | Laser radar point cloud filtering method and device, computer equipment and storage medium | |
| CN105957106B (en) | The method and apparatus of objective tracking | |
| CN109917390A (en) | Vehicle checking method and system based on radar | |
| CN111402299B (en) | Remote sensing image target tracking method and device based on static orbit staring satellite | |
| CN112689775B (en) | Radar point cloud clustering method and device | |
| CN113111513B (en) | Sensor configuration scheme determining method and device, computer equipment and storage medium | |
| CN110837077B (en) | Sound source position verification method and device | |
| CN101794437A (en) | Method for detecting abnormal target in hyperspectral remotely sensed image | |
| CN113835078B (en) | Signal level joint detection method and device based on local three-dimensional grid | |
| EP3353567A1 (en) | Detecting objects in images | |
| US11754704B2 (en) | Synthetic-aperture-radar image processing device and image processing method | |
| US20020097635A1 (en) | Method for target tracking and motion analysis | |
| CN109190647B (en) | Active and passive data fusion method | |
| CN114966591A (en) | Large target detection method, large target detection device and electronic equipment | |
| CN114578313B (en) | Centroid lookup-based grid detection mirror image elimination method and device | |
| RU2740708C1 (en) | Radio monitoring results processing method | |
| RU2659486C1 (en) | Method of the radio monitoring results processing | |
| US10958287B1 (en) | Efficient compression of radar data | |
| CN113344954A (en) | Boundary detection method and device, computer equipment, storage medium and sensor | |
| CN110231602B (en) | Large-batch sea surface target point trace extraction algorithm based on two-dimensional partition processing | |
| CN113034539A (en) | Method and device for determining boundary frame of point cloud | |
| CN117008166A (en) | Positioning quality evaluation method, apparatus, device, storage medium, and program product | |
| CN111008675B (en) | Method and device for sampling and processing recall area | |
| Chong et al. | Tracking multiple air tragets with distributed acoustic sensors | |
| CN110738191B (en) | Object classification method, device, equipment and medium based on sonar signals |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |