CN107302376B - Intelligent building characteristic element database control system - Google Patents

Intelligent building characteristic element database control system Download PDF

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CN107302376B
CN107302376B CN201710459005.4A CN201710459005A CN107302376B CN 107302376 B CN107302376 B CN 107302376B CN 201710459005 A CN201710459005 A CN 201710459005A CN 107302376 B CN107302376 B CN 107302376B
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data
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CN107302376A (en
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湛君毅
陈强
湛楷琦
孟茁超
祝新
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Hunan City University
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Hunan City University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06—Receivers
    • H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
    • H04B1/1027—Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal
    • H04B1/1036—Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal with automatic suppression of narrow band noise or interference, e.g. by using tuneable notch filters
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/02—Transmitters
    • H04B1/04—Circuits
    • H04B1/0475—Circuits with means for limiting noise, interference or distortion
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/0848—Joint weighting
    • H04B7/0854—Joint weighting using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/025—Channel estimation channel estimation algorithms using least-mean-square [LMS] method
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L61/00—Network arrangements, protocols or services for addressing or naming
    • H04L61/09—Mapping addresses
    • H04L61/10—Mapping addresses of different types
    • H04L61/103—Mapping addresses of different types across network layers, e.g. resolution of network layer into physical layer addresses or address resolution protocol [ARP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L2101/00—Indexing scheme associated with group H04L61/00
    • H04L2101/60—Types of network addresses
    • H04L2101/618—Details of network addresses
    • H04L2101/622—Layer-2 addresses, e.g. medium access control [MAC] addresses

Abstract

The invention belongs to the technical field of building element databases, and discloses an intelligent building characteristic element database control system, which is provided with: a wireless transmitter is arranged in the laser scanner; the laser scanner is connected with the wireless receiving station through the wireless transmitter; the wireless receiving station is connected with the post-processing chamber through a wireless transmitter; the post-processing chamber comprises a data processor, a lead and a database memory; the data processor is connected with the database memory through a lead. The invention is an intelligent building characteristic element database control system, by using the system, the scanning and the real-time transmission of the scanned data through a wireless network can be realized, and a post-processing room can rapidly process the data; the efficiency of processing and storing the scanning data is greatly improved; and the data is ensured to be stored quickly, the processing time is shortened, and the working efficiency is improved.

Description

Intelligent building characteristic element database control system
Technical Field
The invention belongs to the technical field of building element databases, and particularly relates to an intelligent building characteristic element database control system.
Background
At present, with the wide application of computers, the computer technology is combined with the traditional landscape architecture protection work to implement digital storage, reproduction and restoration on the traditional landscape architecture, and the traditional landscape architecture is taken as a research object, and the virtual display, the traditional architecture restoration and evolution simulation and other systems of the endangered or extinct landscape architecture are realized by utilizing the technologies such as virtual reality, image processing, artificial intelligence and the like, so that the efficiency and the effect of the traditional landscape architecture protection research are greatly improved; however, the conventional through-scan image needs to be brought back to a post-processing chamber for processing, which requires a long processing time and a complicated process, and data is easily lost in the middle.
In summary, the problems of the prior art are as follows: the data scanned from the field needs to be transported back to a post-processing room for processing, so that the processing time is prolonged, the working efficiency is low, and the data is easily lost in the transporting back process.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an intelligent building characteristic element database control system.
The invention is realized in this way, an intelligent building characteristic element database control system, which is provided with:
a laser scanner;
a wireless transmitter is arranged in the laser scanner;
the echo self-interference self-adaptive suppression method of the wireless transmitter comprises the following specific steps:
the method comprises the following steps: received signal of near-end communication node
Figure BDA0001324413530000011
Comprises the following steps:
tR(n)＝HFE(n)tFE(n)+HNE(n)tNE(n)+w(n)；
wherein the content of the first and second substances,
Figure BDA0001324413530000021
receiving a signal for a desired target from a remote node; while
Figure BDA0001324413530000022
Transmitting a signal, namely an echo self-interference signal, for a near-end node;
Figure BDA0001324413530000023
respectively denote the proximal and distal jth (j ═ N)1,…,NT) A transmit signal on a strip antenna;
Figure BDA0001324413530000024
and
Figure BDA0001324413530000025
channel transfer functions for the far-end and near-end transmit signals, respectively; w (n) is channel additive white gaussian noise; wherein N isTIndicating the number of transmitting antennas of the communication node, NRIs the number of receiving antennas, NfIs the signal per frame length (.)TRepresenting a transposed operation sign on a matrix or vector;
step two: the method comprises the following steps of carrying out self-interference suppression on a received signal mixed with self-interference and channel noise by utilizing a normalized least mean square error (NLMS) algorithm at a receiving end, wherein a cost function of the algorithm is defined as:
Figure BDA0001324413530000026
where Min represents the minimum value, n represents the nth time, and E (E)NE(n))2Representing a near-end error signal
Figure BDA0001324413530000027
Average power of E [ ·]Representing desired operator, tNE(n) denotes an actual transmission signal of the near-end transmission antenna,
Figure BDA0001324413530000028
representing the near-end transmitted signal t obtained after filtering the near-end total received signalNE(n) an estimate of;
step three: setting a correlation initial value for self-interference suppression by adopting a normalized minimum mean square error (NLMS) algorithm:
setting the initial iteration number K to 1, setting the maximum iteration number K and setting the convergence step factor mu according to the autocorrelation matrix of the near-end input signalNEInitialization weight vector alpha of adaptive filterNE(0) And length M of the filter, starting the iterative process, and setting K25, M11, and,
Figure BDA0001324413530000029
μNE＝1；
Step four: root of herbaceous plantAccording to the formula
Figure BDA00013244135300000210
The estimated signal of the near end is obtained according to the following formula
Figure BDA00013244135300000211
The specific process is as follows:
Figure BDA0001324413530000031
wherein j is N1,…,NT，NTRepresenting the total number of transmit antennas, M being the length of the adaptive filter, alphaNE(n) a weight vector at time n,
Figure BDA0001324413530000032
the near-end error signal obtained after adaptive filtering is carried out on the jth receiving antenna at the moment n,
Figure BDA0001324413530000033
receiving signals on a jth near-end receiving antenna;
j<NTthen let j equal to j +1, estimate the estimated signal on the next receiving antenna
Figure BDA0001324413530000034
j＝NTIf yes, go to step five;
step five: updating the weight vector at n time according to the following formula
Figure BDA0001324413530000035
And outputs a near-end transmission signal t according to the iteration resultNE(n) estimated signal
Figure BDA0001324413530000036
The specific process is as follows:
updating the weight vector at the next moment as follows:
Figure BDA0001324413530000037
wherein j is 1, …, NT，NTRepresenting the total number of transmit antennas by a weight vector alphaNE(n) adjustment factor in the iterative process, the size set in the simulation is 0.001,
Figure BDA0001324413530000038
for the received signal on the jth near-end receive antenna,
Figure BDA0001324413530000039
a near-end error signal mu obtained by the j-th receiving antenna at the time n after NLMS self-adaptive filteringNERepresents a convergence step factor, (.)TRepresenting a transpose operator on a matrix or vector;
step six: according to the optimal weight vector alphaNE(n) and the formula:
Figure BDA00013244135300000310
obtaining a near-end estimate signal from the equation
Figure BDA00013244135300000311
The final expression of (1):
Figure BDA00013244135300000312
wherein j is 1, …, NT，NTRepresenting the total number of transmitting antennas, alphaNE(n) represents the weight vector at time n,
Figure BDA0001324413530000041
the weight value of n time is shown, wherein i is 1, …, M, M represents the length of the filter,
Figure BDA0001324413530000042
on the jth receiving antennaThe received signal of (1);
step seven: receiving signal t from ensembleR(n) filtering the estimated echo self-interference signal to obtain a useful transmission signal from the remote node, and sending the signal to a subsequent MIMO decoding detection unit to obtain an accurate estimate of the remote transmission signal, specifically including:
first, from the received signal tR(n) subtracting the echo self-interference estimation signal
Figure BDA0001324413530000043
Obtaining useful transmission signal t from remote nodeES(n) is:
Figure BDA0001324413530000044
second, the signal t is converted into a signalES(n) sending the signal to a subsequent MIMO decoding detection unit to obtain a far-end transmitted signal tFE(n) estimating;
the laser scanner is connected with a wireless receiving station through a wireless transmitter;
the ARP request packet hijacking and answering mechanism of the method for rapidly roaming the multi-gateway terminal in the wireless receiving station comprises the following specific steps:
step one, after receiving an ARP request packet, the MAP node extracts a source mac address, then queries a local conversion table to judge whether the source mac address is in the table, if the source mac address is in the local conversion table, the MAP node indicates a data packet sent by a client connected with the MAP node, and the step two is entered; otherwise, not processing;
step two, after finding out a corresponding local conversion table entry according to the source mac address, extracting a flag domain flag in the local conversion table, carrying out bitwise operation on the flag domain flag and L2P _ NCL _ CLIENT _ WIFI, and if the result is 1, indicating that the data packet is sent out by the WIFI CLIENT, and entering step three; otherwise, not processing;
step three, extracting a target IP address of the ARP request packet, judging whether the target IP address is the MPP node IP address or not, if the target IP address is the MPP node IP, entering step four; otherwise, not processing;
step four, searching whether a response item exists in a local DAT table, if yes, directly generating an ARP response packet for response; otherwise, entering the step five;
step five, acquiring a mac address of the MPP node selected by the MAP node, and using the mac address as a response to construct an ARP response packet to be sent to an ARP requester;
the wireless receiving station is connected with the post-processing chamber through a wireless transmitter;
the post-processing chamber calculates the node to be positioned and the anchor node A according to a logarithmic distance path loss model by the following formulaiThe distance between:
Pr(di)＝Pr(d0)-10·γlg(di)+Xσ
wherein, Pr (d)i') indicates a distance d from the transmitting endi' time derived cross-correlation value, Pr (d)0) Indicating distance from sender d0A cross-correlation value obtained at 1 meter, γ represents a path loss factor, lg (·) represents a logarithmic operation X with a base of 10σObeying a Gaussian distribution with a mean value of 0 and a standard deviation of sigma;
the distances d between each anchor node and the node O to be positioned are calculated by the formulai' the coordinates of the corresponding anchor nodes are A respectivelyi(xi,yi) Where i is 0,1,2, …, n;
the post-processing chamber comprises a data processor, a lead and a database memory;
the data processor is connected with the database memory through a lead.
Further, the connecting wires of the data processor and the memory are protected by a plastic shell;
the data compression method of the data processor comprises the following steps:
step one, during encoding, according to E1n+1＝E1n+dn+1Calculating the value of E1 according to the formula
Figure BDA0001324413530000051
And
Figure BDA0001324413530000052
calculating a fitting residual error by using the formula, wherein in the two steps of calculation, the result needs to be subjected to out-of-limit judgment, and whether E1 is out-of-limit is judged to avoid overflow caused by exceeding the upper limit of a sensor data bus; judging whether the residual error exceeds the limit or not to realize the piecewise fitting;
step two, when the fitting residual error of a section of input data is completely calculated, constructing { dn,E1n,DFR3,DFR4,…DFRnThe data packet shown in the description is entropy-coded by an S-Huffman coding method and then sent out, and when a receiving end decodes, a group of received data is decoded to restore { d }n,E1n,DFR3,DFR4,…DFRnData packets of the formula, according to
Figure BDA0001324413530000053
And (4) calculating and restoring all original data by using the formula.
Further, the wireless transmitter is located at the inner lower right corner of the laser scanner.
The invention has the advantages and positive effects that: by using the system, the scanned data can be transmitted in real time through a wireless network while scanning, and a post-processing chamber can rapidly process the data; the efficiency of processing and storing the scanning data is greatly improved; and the data is ensured to be stored quickly, the processing time is shortened, and the working efficiency is improved.
Drawings
FIG. 1 is a schematic structural diagram of an intelligent building characteristic element database control system provided by an embodiment of the invention;
in the figure: 1. a laser scanner; 2. a wireless transmitter; 3. a wireless receiving station; 4. a post-processing chamber; 4-1, a data processor; 4-2, conducting wires; 4-3, database memory.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings.
The structure of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in the figure: a wireless transmitter 2 is arranged in the laser scanner 1; the laser scanner 1 is connected with a wireless receiving station 3 through a wireless transmitter 2; the wireless receiving station 3 is connected with the post-processing chamber 4 through the wireless transmitter 2; the post-processing chamber 4 comprises a data processor 4-1, a lead 4-2 and a database memory 4-3; the data processor 4-1 is connected to the database memory 4-3 by a lead 4-2.
The echo self-interference self-adaptive suppression method of the wireless transmitter comprises the following specific steps:
the method comprises the following steps: received signal of near-end communication node
Figure BDA0001324413530000061
Comprises the following steps:
tR(n)＝HFE(n)tFE(n)+HNE(n)tNE(n)+w(n)；
wherein the content of the first and second substances,
Figure BDA0001324413530000062
receiving a signal for a desired target from a remote node; while
Figure BDA0001324413530000063
Transmitting a signal, namely an echo self-interference signal, for a near-end node;
Figure BDA0001324413530000064
respectively denote the proximal and distal jth (j ═ N)1,…,NT) A transmit signal on a strip antenna;
Figure BDA0001324413530000071
and
Figure BDA0001324413530000072
channel transfer functions for the far-end and near-end transmit signals, respectively; w (n) is channel additive white gaussian noise; wherein N isTIndicating the number of transmitting antennas of the communication node, NRIs the number of receiving antennas, NfIs the signal per frame length (.)TRepresenting a transposed operation sign on a matrix or vector;
step two: the method comprises the following steps of carrying out self-interference suppression on a received signal mixed with self-interference and channel noise by utilizing a normalized least mean square error (NLMS) algorithm at a receiving end, wherein a cost function of the algorithm is defined as:
Figure BDA0001324413530000073
where Min represents the minimum value, n represents the nth time, and E (E)NE(n))2Representing a near-end error signal
Figure BDA0001324413530000074
Average power of E [ ·]Representing desired operator, tNE(n) denotes an actual transmission signal of the near-end transmission antenna,
Figure BDA0001324413530000075
representing the near-end transmitted signal t obtained after filtering the near-end total received signalNE(n) an estimate of;
step three: setting a correlation initial value for self-interference suppression by adopting a normalized minimum mean square error (NLMS) algorithm:
setting the initial iteration number K to 1, setting the maximum iteration number K and setting the convergence step factor mu according to the autocorrelation matrix of the near-end input signalNEInitialization weight vector alpha of adaptive filterNE(0) And length M of the filter, starting the iterative process, and setting K25, M11, and,
Figure BDA0001324413530000076
μNE＝1；
Step four: according to the formula
Figure BDA0001324413530000077
The estimated signal of the near end is obtained according to the following formula
Figure BDA0001324413530000078
The specific process is as follows:
Figure BDA0001324413530000079
wherein j is N1,…,NT，NTRepresenting the total number of transmit antennas, M being the length of the adaptive filter, alphaNE(n) a weight vector at time n,
Figure BDA0001324413530000081
the near-end error signal obtained after adaptive filtering is carried out on the jth receiving antenna at the moment n,
Figure BDA0001324413530000082
receiving signals on a jth near-end receiving antenna;
j<NTthen let j equal to j +1, estimate the estimated signal on the next receiving antenna
Figure BDA0001324413530000083
j＝NTIf yes, go to step five;
step five: updating the weight vector at n time according to the following formula
Figure BDA0001324413530000084
And outputs a near-end transmission signal t according to the iteration resultNE(n) estimated signal
Figure BDA0001324413530000085
The specific process is as follows:
updating the weight vector at the next moment as follows:
Figure BDA0001324413530000086
wherein j is 1, …, NT，NTRepresenting the total number of transmit antennas by a weight vector alphaNE(n) adjustment factors in an iterative procedure, in simulationThe set size is 0.001,
Figure BDA0001324413530000087
for the received signal on the jth near-end receive antenna,
Figure BDA0001324413530000088
a near-end error signal mu obtained by the j-th receiving antenna at the time n after NLMS self-adaptive filteringNERepresents a convergence step factor, (.)TRepresenting a transpose operator on a matrix or vector;
step six: according to the optimal weight vector alphaNE(n) and the formula:
Figure BDA0001324413530000089
obtaining a near-end estimate signal from the equation
Figure BDA00013244135300000810
The final expression of (1):
Figure BDA00013244135300000811
wherein j is 1, …, NT，NTRepresenting the total number of transmitting antennas, alphaNE(n) represents the weight vector at time n,
Figure BDA00013244135300000812
the weight value of n time is shown, wherein i is 1, …, M, M represents the length of the filter,
Figure BDA00013244135300000813
representing the received signal on the jth receiving antenna;
step seven: receiving signal t from ensembleR(n) filtering the estimated echo self-interference signal to obtain a useful transmission signal from the remote node, and sending the signal to a subsequent MIMO decoding detection unit to obtain an accurate estimate of the remote transmission signal, specifically including:
first, from the received signal tR(n) subtracting the echo self-interference estimation signal
Figure BDA0001324413530000091
Obtaining useful transmission signal t from remote nodeES(n) is:
Figure BDA0001324413530000092
second, the signal t is converted into a signalES(n) sending the signal to a subsequent MIMO decoding detection unit to obtain a far-end transmitted signal tFE(n) estimating;
the laser scanner is connected with a wireless receiving station through a wireless transmitter;
the ARP request packet hijacking and answering mechanism of the method for rapidly roaming the multi-gateway terminal in the wireless receiving station comprises the following specific steps:
step one, after receiving an ARP request packet, the MAP node extracts a source mac address, then queries a local conversion table to judge whether the source mac address is in the table, if the source mac address is in the local conversion table, the MAP node indicates a data packet sent by a client connected with the MAP node, and the step two is entered; otherwise, not processing;
step two, after finding out a corresponding local conversion table entry according to the source mac address, extracting a flag domain flag in the local conversion table, carrying out bitwise operation on the flag domain flag and L2P _ NCL _ CLIENT _ WIFI, and if the result is 1, indicating that the data packet is sent out by the WIFI CLIENT, and entering step three; otherwise, not processing;
step three, extracting a target IP address of the ARP request packet, judging whether the target IP address is the MPP node IP address or not, if the target IP address is the MPP node IP, entering step four; otherwise, not processing;
step four, searching whether a response item exists in a local DAT table, if yes, directly generating an ARP response packet for response; otherwise, entering the step five;
step five, acquiring a mac address of the MPP node selected by the MAP node, and using the mac address as a response to construct an ARP response packet to be sent to an ARP requester;
the wireless receiving station is connected with the post-processing chamber through a wireless transmitter;
the post-processing chamber calculates the node to be positioned and the anchor node A according to a logarithmic distance path loss model by the following formulaiThe distance between:
Pr(di)＝Pr(d0)-10·γlg(di)+Xσ
wherein, Pr (d)i') indicates a distance d from the transmitting endi' time derived cross-correlation value, Pr (d)0) Indicating distance from sender d0A cross-correlation value obtained at 1 meter, γ represents a path loss factor, lg (·) represents a logarithmic operation X with a base of 10σObeying a Gaussian distribution with a mean value of 0 and a standard deviation of sigma;
the distances d between each anchor node and the node O to be positioned are calculated by the formulai' the coordinates of the corresponding anchor nodes are A respectivelyi(xi,yi) Where i is 0,1,2, …, n;
the data compression method of the data processor comprises the following steps:
step one, during encoding, according to E1n+1＝E1n+dn+1Calculating the value of E1 according to the formula
Figure BDA0001324413530000101
And
Figure BDA0001324413530000102
calculating a fitting residual error by using the formula, wherein in the two steps of calculation, the result needs to be subjected to out-of-limit judgment, and whether E1 is out-of-limit is judged to avoid overflow caused by exceeding the upper limit of a sensor data bus; judging whether the residual error exceeds the limit or not to realize the piecewise fitting;
step two, when the fitting residual error of a section of input data is completely calculated, constructing { dn,E1n,DFR3,DFR4,…DFRnThe data packet shown in the description is entropy-coded by an S-Huffman coding method and then sent out, and when a receiving end decodes, a group of received data packets are firstly codedDecoding the data to restore { dn,E1n,DFR3,DFR4,…DFRnData packets of the formula, according to
Figure BDA0001324413530000103
And (4) calculating and restoring all original data by using the formula.
The working principle of the invention is as follows:
after the laser scanner scans the building, the data are sent out through the wireless transmitter, at the moment, the wireless receiving station transmits the acquired information to a farther place, the post-processing room receives the scanned data through wireless, and the data processor processes the acquired data and sends the processed data to the database storage.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.

Claims (3)

1. The utility model provides an intelligence building characteristic element database control system which characterized in that, intelligence building characteristic element database control system is provided with:
a laser scanner;
a wireless transmitter is arranged in the laser scanner;
the echo self-interference self-adaptive suppression method of the wireless transmitter comprises the following specific steps:
the method comprises the following steps: received signal of near-end communication node
Figure FDA0002707656260000011
Comprises the following steps:
tR(n)＝HFE(n)tFE(n)+HNE(n)tNE(n)+w(n)；
wherein the content of the first and second substances,
Figure FDA0002707656260000012
from a remote nodeReceiving a signal with a target; while
Figure FDA0002707656260000013
Transmitting a signal, namely an echo self-interference signal, for a near-end node;
Figure FDA0002707656260000014
indicating the transmitted signal on the jth antenna at the near end and the far end, respectively, j being N1,…,NT；
Figure FDA0002707656260000015
And
Figure FDA0002707656260000016
channel transfer functions for the far-end and near-end transmit signals, respectively; w (n) is channel additive white gaussian noise; wherein N isTIndicating the number of transmitting antennas of the communication node, NRIs the number of receiving antennas, NfIs the signal per frame length (.)TRepresenting a transposed operation sign on a matrix or vector;
step two: the method comprises the following steps of carrying out self-interference suppression on a received signal mixed with self-interference and channel noise by utilizing a normalized least mean square error (NLMS) algorithm at a receiving end, wherein a cost function of the algorithm is defined as:
Figure FDA0002707656260000017
where Min represents the minimum value, n represents the nth time, and E [ (E)NE(n))2]Representing a near-end error signal
Figure FDA0002707656260000018
Average power of E [ ·]Representing desired operator, tNE(n) denotes an actual transmission signal of the near-end transmission antenna,
Figure FDA0002707656260000019
indicating total connection to the near endAfter the received signal is filtered, the obtained signal t is transmitted to the near endNE(n) an estimate of;
step three: setting a correlation initial value for self-interference suppression by adopting a normalized minimum mean square error (NLMS) algorithm:
setting the initial iteration number K to 1, setting the maximum iteration number K and setting the convergence step factor mu according to the autocorrelation matrix of the near-end input signalNEInitialization weight vector alpha of adaptive filterNE(0) And length M of the filter, starting the iterative process, and setting K25, M11, and,
Figure FDA0002707656260000021
μNE＝1；
Step four: according to the formula
Figure FDA0002707656260000022
Estimating a signal at a near end
Figure FDA0002707656260000023
Step five: updating the weight vector at n time according to the following formula
Figure FDA0002707656260000024
And outputs a near-end transmission signal t according to the iteration resultNE(n) estimated signal
Figure FDA0002707656260000025
The specific process is as follows:
updating the weight vector at the next moment as follows:
Figure FDA0002707656260000026
wherein j is 1, …, NT，NTRepresenting the total number of transmit antennas by a weight vector alphaNE(n) adjustment factor in the iterative process, the size set in the simulation being0.001，
Figure FDA0002707656260000027
For the received signal on the jth near-end receive antenna,
Figure FDA0002707656260000028
a near-end error signal mu obtained by the j-th receiving antenna at the time n after NLMS self-adaptive filteringNERepresents a convergence step factor, (.)TRepresenting a transpose operator on a matrix or vector;
step six: according to the optimal weight vector alphaNE(n) and the formula:
Figure FDA0002707656260000029
obtaining a near-end estimate signal from the equation
Figure FDA00027076562600000210
The final expression of (1):
Figure FDA00027076562600000211
wherein j is 1, …, NT，NTRepresenting the total number of transmitting antennas, alphaNE(n) represents the weight vector at time n,
Figure FDA00027076562600000212
the weight value of n time is shown, wherein i is 1, …, M, M represents the length of the filter,
Figure FDA00027076562600000213
representing the received signal on the jth receiving antenna;
step seven: receiving signal t from ensembleR(n) filtering the estimated echo self-interference signal to obtain a useful transmission signal from the remote node, and sending the useful transmission signal to the subsequent nodesThe MIMO decoding detection unit to obtain an accurate estimate of the far-end transmitted signal specifically includes:
first, from the received signal tR(n) subtracting the echo self-interference estimation signal
Figure FDA0002707656260000031
Obtaining useful transmission signal t from remote nodeES(n) is:
Figure FDA0002707656260000032
second, the signal t is converted into a signalES(n) sending the signal to a subsequent MIMO decoding detection unit to obtain a far-end transmitted signal tFE(n) estimating;
the laser scanner is connected with a wireless receiving station through a wireless transmitter;
the ARP request packet hijacking and answering mechanism of the method for rapidly roaming the multi-gateway terminal in the wireless receiving station comprises the following specific steps:
step one, after receiving an ARP request packet, the MAP node extracts a source mac address, then queries a local conversion table to judge whether the source mac address is in the table, if the source mac address is in the local conversion table, the MAP node indicates a data packet sent by a client connected with the MAP node, and the step two is entered; otherwise, not processing;
step two, after finding out a corresponding local conversion table entry according to the source mac address, extracting a flag domain flag in the local conversion table, carrying out bitwise operation on the flag domain flag and L2P _ NCL _ CLIENT _ WIFI, and if the result is 1, indicating that the data packet is sent out by the WIFI CLIENT, and entering step three; otherwise, not processing;
step three, extracting a target IP address of the ARP request packet, judging whether the target IP address is the MPP node IP address or not, if the target IP address is the MPP node IP, entering step four; otherwise, not processing;
step four, searching whether a response item exists in a local DAT table, if yes, directly generating an ARP response packet for response; otherwise, entering the step five;
step five, acquiring a mac address of the MPP node selected by the MAP node, and using the mac address as a response to construct an ARP response packet to be sent to an ARP requester;
the wireless receiving station is connected with the post-processing chamber through a wireless transmitter;
the post-processing chamber calculates the node to be positioned and the anchor node A according to a logarithmic distance path loss model by the following formulaiThe distance between:
Pr(d′i)＝Pr(d0)-10·γlg(d′i)+Xσ
wherein, Pr (d'i) Representing distance d 'from transmitting end'iTime-derived cross-correlation value, Pr (d)0) Indicating distance from sender d0The cross-correlation value obtained at 1 meter, γ represents the path loss factor, lg (·) represents a logarithmic operation with a base of 10, XσObeying a Gaussian distribution with a mean value of 0 and a standard deviation of sigma;
calculating the distances d 'between each anchor node and the node O to be positioned by utilizing the formula'iThe coordinates of the corresponding anchor nodes are respectively Ai(xi,yi) Where i is 0,1,2, …, n;
the post-processing chamber comprises a data processor, a lead and a database memory;
the data processor is connected with the database memory through a lead.
2. The intelligent architectural feature element database control system of claim 1, wherein the connecting wires of said data processor and memory are protected by a plastic housing;
the data compression method of the data processor comprises the following steps:
step one, during encoding, according to E1n+1＝E1n+dn+1Calculating the value of E1 according to the formula
Figure FDA0002707656260000041
And
Figure FDA0002707656260000042
calculating a fitting residual error by using the formula, wherein in the two steps of calculation, the result needs to be subjected to out-of-limit judgment, and whether E1 is out-of-limit is judged to avoid overflow caused by exceeding the upper limit of a sensor data bus; judging whether the residual error exceeds the limit or not to realize the piecewise fitting;
wherein E1 is PCM code; e1n+1And E1nRespectively the number of the n +1 th coding line and the number of the n-th coding line; dn+1Displacement in two frame interval time;
step two, when the fitting residual error of a section of input data is completely calculated, constructing { dn,E1n,DFR3,DFR4,…DFRnThe data packet shown in the description is entropy coded by an S-Huffman coding method and then sent out, and when a receiving end decodes, a group of received data is decoded first to restore { d }n,E1n,DFR3,DFR4,…DFRnData packets of the formula, according to
Figure FDA0002707656260000043
Calculating and restoring all original data by using the formula;
wherein d isnDisplacement in two frame interval time; e1nThe number of the nth coding line is; DFRnIs the differential.
3. The intelligent building feature element database control system of claim 1, wherein the wireless transmitter is located at the lower right corner inside the laser scanner.
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