CN114866165B - Rapid acquisition method for multi-band indoor signal distribution field - Google Patents
Rapid acquisition method for multi-band indoor signal distribution field Download PDFInfo
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Abstract
The invention discloses a rapid acquisition method for a multi-band indoor signal distribution field. Step 1: an LFM signal source is arranged indoors; step 2: based on the LFM signal source in the step 1, performing drive test sampling by using receiving equipment; step 3: determining the position of a receiver based on the drive test sampling result in the step 2; step 4: and (3) utilizing the receiver for determining the position in the step (3) to perform signal processing and output a measurement result. The invention overcomes the problems of operational complexity, model universality and measurement accuracy.
Description
Technical Field
The invention belongs to the field of signal coverage measurement; in particular to a rapid acquisition method of a multi-band indoor signal distribution field.
Background
Currently, there are mainly several solutions to the problem of signal coverage measurement: 1) The method relies on the mode that the user product reports to the mobile operator; 2) Minimization of drive tests (DRIVE TEST, MDT) based on environmental electromagnetic maps (Radio Environment Maps, REMs); 3) Based on ray tracing or ray emission schemes. The scheme based on user product reporting is not in the discussion range of the scheme due to low efficiency and low accuracy. The remaining two ways are briefly described below.
1) Environment electromagnetic diagram-based minimization of drive test scheme
The basic principle of such a scheme is mainly that the user equipment periodically reports the geographical location to the network operator and makes relevant measurements during the course of the communication. The difference between the traditional drive test mode and MDT is that the traditional scheme adopts the positioning of user equipment based on a base station (base station level); whereas absolute geographical location information (GPS level) is used in MDT.
In an indoor environment, the main drawbacks of such a solution are: first, GPS information is not available and base station based positioning is very inaccurate. Because the obstacles in the indoor environment are densely distributed, the electromagnetic environment is complex, the signal distortion of the base station and the GPS is extremely serious, the positioning result error is extremely high, and the positioning result error cannot be effectively used as a reference. In environments such as underground parking stations or subway stations, even GPS signals cannot be received effectively, and therefore there are obvious disadvantages. Secondly, due to the complex electromagnetic environment, the multipath effect is obvious, and the phenomenon of 'pseudo blind area' with smaller signal receiving intensity can also occur at a plurality of positions which are not signal receiving blind areas due to the influence of multipath deep fading.
2) Scheme based on ray tracing and other prediction models
The scheme mainly adopts modeling of a scene to be measured in a signal distribution field to obtain physical propagation information such as indoor obstacle distribution, wall size distribution, loss coefficients of various obstacle materials, indoor signal attenuation coefficients and the like. And simulating the physical propagation of the signal, thereby obtaining the signal receiving intensity simulation result of the whole scene. In the operation process, the propagation process of the signal is equivalent to rays, and physical properties such as ray reflection, refraction and scattering are mainly adopted, so that the signal is called ray tracing.
In an indoor actual measurement environment, the disadvantages of using such a scheme are mainly expressed as follows: first, scene modeling needs to be performed accurately, and different modeling is needed for different scenes, and the parameter measurement process is very complex. Thus, the protocol is not universal. Secondly, the operation complexity is high, and in order to obtain an accurate result, the higher the number of ray tracing is, the greater the accuracy is, so that extremely high calculation force is needed to meet the requirement.
Disclosure of Invention
The invention provides a rapid acquisition method of a multi-band indoor signal distribution field, which solves the problems of operation complexity, model universality and measurement accuracy, and can rapidly and accurately acquire a signal receiving intensity measurement result of a designated area.
The invention is realized by the following technical scheme:
a rapid acquisition method for a multi-band indoor signal distribution field, the rapid acquisition method comprising the following steps:
Step 1: an LFM signal source is arranged indoors;
Step 2: based on the LFM signal source in the step 1, performing drive test sampling by using receiving equipment;
Step 3: determining the position of a receiver based on the drive test sampling result in the step 2;
step 4: and (3) utilizing the receiver for determining the position in the step (3) to perform signal processing and output a measurement result.
Furthermore, the step 1 specifically includes that the LFM signal source is composed of a radio frequency device for transmitting a linear frequency modulation signal and a control upper computer; the signal source can continuously send the linear frequency modulation signal with the initial frequency of f 1 and the ending frequency of f 2, and the mathematical expression of the LFM signal is as follows:
where Re { } represents the real part and T is the pulse period.
Further, the step 2 is specifically that the receiving device is composed of a receiver for receiving radio frequency signals and an upper computer for storing the received signals; during reception, the device samples the received signal for at least more than one pulse period TThe information is sent to an upper computer for storage, the upper computer records the coordinate information x of the current position when storing, and the information x and the received signal of the point are combined into a two-dimensional tuple/>Stored in a database.
Further, in the step 3, in a process of determining a position of the receiver, a signal source is turned on, and the receiving device moves and receives a chirp signal;
the determined location schemes include, but are not limited to, pre-measured and calibrated sampling location recording schemes or Ultra Wideband (UWB) based high precision indoor positioning.
Further, the step 4 specifically includes the following steps,
Step 4.1: preprocessing a signal received by a receiver;
Step 4.2: interpolation recovery of the signal reception intensity field is performed on the preprocessed signal.
Further, in the step 4.1, the focusing of the LFM signal is performed by using fractional fourier transform,
Step 4.1.1: for received signalsCarrying out energy focusing in the corresponding optimal fractional Fourier transform domain;
step 4.1.2: collecting the energy of each multipath peak of energy focusing and searching and superposing;
step 4.1.3: and taking the superposition value in the step 4.1.2 as the received signal energy value of the current position.
Further, the process of performing focus peak positioning in the optimal fractional fourier transform domain in step 4.1.1 is specifically to use a focus peak searching method including, but not limited to, a data size comparison method about a peak value and a zero crossing counting method for binarizing at a given threshold value;
The peak obtained through searching is converted into a time domain amplitude according to the conversion relation between the time domain and the fractional domain:
Wherein v max is the coordinate position of a certain peak value of the LFM signal transformation result in the optimal fractional domain, and X pmax(νmax) is the amplitude of the peak value in the fractional domain; n is the number of signal sampling data points, sin () represents a sine function; a is the time domain amplitude value corresponding to the fractional domain peak value; p max is the optimal fractional Fourier transform order corresponding to the transmitted LFM signal;
Frequency modulation slope of p max and LFM signals The relation between the two is:
Wherein f 1 is the initial frequency at which the signal source can continuously transmit, and f 2 is the termination frequency at which the signal source can continuously transmit; t is the pulse period; cot () is a cotangent function;
The time-domain amplitudes of the respective peaks are superimposed as a current signal reception intensity value s x, and the values are stored together with the position in a two-dimensional tuple (x, s x) for storage.
Further, the interpolation recovery procedure of step 4.2 is specifically that the sampled data of all the sampling points (1, 2, 3.) are sequentially arranged and expressed as (x|y):
For the unknown point position X *, the predicted result mean μ (y *|X*, X, y) of the signal reception intensity value y * thereof is obtained by the following equation:
Where k (X *, X) is the result of the calculation of the kernel function employed at positions X * and X, Is the observation noise of the environment, I is the identity matrix, () -1 is the inversion operation of the matrix;
The uncertainty of the prediction is expressed by the variance σ 2(y*|X*, X, y) of the prediction result:
the beneficial effects of the invention are as follows:
The invention provides a low-cost and flexible-control indoor signal field measuring and acquiring method, which has obvious advantages of flexibility and high efficiency compared with the traditional drive test and user reporting modes which are highly dependent on professional skills.
The invention can effectively solve the problem of measurement errors introduced by the indoor complex electromagnetic environment, obtain smooth signal field distribution and have good resistance effect on the indoor strong multipath effect.
The invention adopts the scheme of combining sampling and prediction, can effectively reduce the number of the arranged sampling nodes, improves the measurement efficiency and reduces the measurement time.
Drawings
Fig. 1 is a flow chart of the operation of the present invention.
Fig. 2 is a diagram of the transceiver of the present invention, wherein (a) the transmitter is shown and (b) the receiver is shown.
Fig. 3 is a schematic view of an application scenario of the present invention.
Fig. 4 is a diagram of an actual test scenario of the present invention, wherein (a) the gate left side scenario (facing the gate) and (b) the gate right side scenario (facing the gate).
Fig. 5 is a diagram of a transmitter structure used in the present invention.
Fig. 6 is a block diagram of a receiver used in the present invention.
Fig. 7 is a diagram of the time domain waveform and fractional domain focusing result of the actual received signal according to the present invention, wherein (a) the time domain waveform is shown under the multipath effect, and (b) the optimum fractional domain focusing result is shown under the multipath effect.
Fig. 8 is a graph of reconstructed sample node distribution for (a) median filtered sample processing results and (b) sample processing results according to the present invention.
Fig. 9 is a graph of the results of the reconstruction of the signal received intensity field of the present invention, wherein (a) is a graph of the results of the median filtering reconstruction and (b) is a graph of the results of the reconstruction of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The workflow is shown in fig. 1, and the method for rapidly acquiring the multi-band indoor signal distribution field comprises the following steps:
Step 1: an LFM signal source is arranged indoors;
Step 2: based on the LFM signal source in the step 1, performing drive test sampling by using receiving equipment;
Step 3: determining the position of a receiver based on the drive test sampling result in the step 2;
step 4: and (3) utilizing the receiver for determining the position in the step (3) to perform signal processing and output a measurement result.
Furthermore, the step 1 specifically includes that the LFM signal source is composed of a radio frequency device for transmitting a linear frequency modulation (Linear Frequency Modulated, LFM) signal and a control upper computer; the signal source can continuously send the linear frequency modulation signal with the initial frequency of f 1 and the ending frequency of f 2, and the mathematical expression of the LFM signal is as follows:
where Re { } represents the real part and T is the pulse period.
In the actual test process, f 1 and f 2 are adjusted according to the signal field distribution test requirements of different frequency bands, so that the purpose of multi-frequency band measurement is achieved; the placement position of the signal source is determined by actual requirements.
Further, the step 2 is specifically that the receiving device is composed of a receiver for receiving radio frequency signals and an upper computer for storing the received signals; during reception, the device samples the received signal for at least more than one pulse period TThe information is sent to an upper computer for storage, the upper computer records the coordinate information x of the current position when storing, and the information x and the received signal of the point are combined into a two-dimensional tuple/>Stored in a database.
Further, in the step 3, in a process of determining a position of the receiver, a signal source is turned on, and the receiving device moves and receives a chirp signal;
the determined location schemes include, but are not limited to, pre-measured and calibrated sampling location recording schemes or ultra wideband UWB based high precision indoor positioning.
Further, the step 4 specifically includes the following steps,
Step 4.1: preprocessing a signal received by a receiver;
step 4.2: interpolation recovery of the received intensity field is performed on the preprocessed signal.
Further, due to the complexity of the indoor electromagnetic environment, the multipath effect is very obvious, and the signal may be strengthened or weakened at the receiving position according to the relative size of the propagation path difference and the wavelength between the multipath components. This causes a slight shift in the sampling point which leads to a drastic change in the amplitude of the received signal. Therefore, the intensity value of the direct sampling result of the received signal cannot be used as the signal receiving intensity judgment standard of the current point, so that the pretreatment of the received signal is required;
Step 4.1, the focusing of the LFM signal is performed by using fractional Fourier transform,
Step 4.1.1: for received signalsCarrying out energy focusing in the corresponding optimal fractional Fourier transform domain, wherein the energy focusing is used for focusing peak/pulse;
step 4.1.2: collecting the energy of each multipath peak of energy focusing and searching and superposing;
step 4.1.3: and taking the superposition value in the step 4.1.2 as the received signal energy value of the current position.
Further, the adopted fractional Fourier transform numerical calculation method comprises, but is not limited to, four-term weighted fractional Fourier transform, fractional Fourier transform based on eigenvalue decomposition, closed fractional Fourier transform and other algorithms. The process of performing the focus peak positioning in the optimal fractional fourier transform domain in step 4.1.1 is specifically, a focus peak searching method including, but not limited to, a data size comparison method about a peak (i.e., a method for performing a left-right ortho-position comparison of a data point to position a peak position by using a peak as a highest point property in a local range); a zero crossing count method with binarization at a given threshold; that is, a scheme in which given data is binarized by a threshold value of 0-1, and then the position of the peak is obtained by recording the position of the unidirectional zero crossing, and the like.
The peak obtained through searching is converted into a time domain amplitude according to the conversion relation between the time domain and the fractional domain:
Wherein v max is the coordinate position of a certain peak value of the LFM signal transformation result in the optimal fractional domain, and X pmax(νmax) is the amplitude of the peak value in the fractional domain; n is the number of signal sampling data points, sin () represents a sine function; a is the time domain amplitude value corresponding to the fractional domain peak value; p max is the optimal fractional Fourier transform order corresponding to the transmitted LFM signal;
Frequency modulation slope of p max and LFM signals The relation between the two is:
Wherein f 1 is the initial frequency at which the signal source can continuously transmit, and f 2 is the termination frequency at which the signal source can continuously transmit; t is the pulse period; cot () is a cotangent function;
The time-domain amplitudes of the respective peaks are superimposed as a current signal reception intensity value s x, and the values are stored together with the position in a two-dimensional tuple (x, s x) for storage.
Further, the interpolation recovery process in step 4.2 is specifically aimed at reducing the number of sampling points, and using a small number of sampling point results (x, s x), the signal receiving intensity prediction in the remaining range is performed by the prediction model. The interpolation recovery of the received intensity field is carried out by adopting a Gaussian process regression model, and kernel functions adopted in the prediction process comprise, but are not limited to, rational secondary kernels in various forms, gaussian kernels, materrn covariance function classes and kernels formed by combining the kernel functions. Sample data for all sample points (1, 2, 3.) are sequentially arranged and expressed as (x|y):
For the unknown point position X *, the predicted result mean μ (y *|X*, X, y) of the signal reception intensity value y * thereof is obtained by the following equation:
Where k (X *, X) is the result of the calculation of the kernel function employed at positions X * and X, Is the observation noise of the environment, I is the identity matrix, () -1 is the inversion operation of the matrix;
The uncertainty of the prediction is expressed by the variance σ 2(y*|X*, X, y) of the prediction result:
Example 2
The demonstration verification scene is an indoor scene of 2A 1018 rooms of the Harbin industrial university discipline, and the scene setting schematic diagram and the actual scene are shown in fig. 3 and 4 respectively.
In fig. 3, the floor area on the left side of the gate is about 25.2m 2 and the floor area on the right side is about 12.6m 2. The transmitter is positioned on the desk to the right of the gate of fig. 3 and the receiver samples randomly in the scene. To artificially create a communication blind zone, the gate was closed during the test. Because the gate is made of metal, signals are greatly attenuated under the electromagnetic shielding effect when passing through the gate, and a communication blind area is formed at the other side of the gate. The specific test process is as follows: 1. the transmitter is fixed at the scene location shown in fig. 3 and then transmits a chirped (LFM) signal in cycles. 2. The receiver adopts a trolley to push random discrete sparse sampling in a scene. And when sampling is carried out, recording the sampled position information and the sampled linear frequency modulation signal data, and storing the linear frequency modulation signal data into a preset data format after all the sampling is finished for later processing. 3. All the sampled data are imported into a notebook computer, the whole subsequent signal processing process (mainly aiming at multipath effect) is completed under the assistance of Python and MATLAB, and the signal distribution condition of the whole scene is obtained through reconstruction according to the discrete sampling result. Detailed transmitter and receiver construction, signal generation and acquisition, and data processing procedures will be described separately.
1. Transceiver configuration and signal generation and acquisition process
The transceiver is composed of a National Instruments USRP-2920 device connected with an upper computer (notebook computer) through an Ethernet port. The USRP is responsible for sending (receiving) the linear frequency modulation signals, the upper computer plays roles of parameter configuration, receiving and transmitting control and receiving data storage in the experimental process, and parameter setting and control commands are sent to the USRP through an Ethernet port. During the experiment, the transmitter is fixed on the test stand and kept still. The receiver is placed on an experimental trolley with a length, width and height of 90cm, 70cm and 70cm respectively, and then the transmitter signals at different positions in the test environment are received by mobile measurement. The received signal data information and the current receiving position are stored in an upper computer, and the signal processing process is carried out after the receiving is completed. The transceiver is constructed as shown in fig. 2.
The parameter configuration of the radio signal of the transceiver is completed by Labview software control, and the structure of the transmitter is shown in fig. 5. The whole transmitter can be divided into a baseband Linear Frequency Modulation (LFM) signal generator and a radio frequency USRP interface module which modulates the LFM signal into Labview. The generation of the LFM signal is mainly implemented by the ramp signal generator in fig. 5. It receives four parameters, namely the number of samples, the start frequency, the end frequency and the linear sample type. It should be noted that in inputting the parameters, the value of the number of samples divided by the value of the duration is actually the sampling rate at which the LFM signal is sampled. In order for the transmitted sample to recover the waveform of the LFM signal, this calculated sample rate should be at least 5-10 times the termination frequency of the input. Let f 1 be the start frequency, f 2 be the end frequency, T be the duration, and n be the number of samples. Can be used for deriving the frequency modulation slope
After the two signals are generated, the phases of the two signals multiplied as complex exponential signals are connected to the phase input of the polar to complex conversion module. To prevent overflow errors in the USRP internal DSP, the amplitude of the baseband complex signal should not exceed 1, so the amplitude of the complex exponential signal is set to 1. After this polar to complex conversion, the signal is input to the interface module of the USRP. The USRP interface module is mainly composed of four sub-modules: niUSRP Open Tx Session.vi, niUSRP Configure Signal.vi, niUSRP Write Tx Data.vi and niUSRP Close Session.vi. The niUSRP Open Tx session.vi accepts the device name parameter (mainly the IP address of the USRP) and starts a transmission session niUSRP Configure signal.vi between the host and the USRP for signal transmission parameters and signal samples, accepts parameters related to signal transmission, such as IQ symbol rate, carrier frequency, antenna name and antenna gain for implementing transmission, and the like, from the input control of the front panel, and sends the configuration parameter to the USRP. niUSRPWrite Tx data.vi accepts the previously generated LFM signal sample data and sends it to the USRP. And niUSRP Close session. Vi ends the session and reports possible errors after completing the data transfer between the host and USRP as described above. After the configuration parameters and the transmission of the signal samples are completed, the USRP configures the baseband signals according to the parameters, processes the baseband signals through a radio frequency link and then transmits the baseband signals from the antenna.
The receiver structure is shown in fig. 6. The receiver part mainly comprises five sub-modules corresponding to the transmitting end: niUSRP Open Rx Session.vi, niUSRP Configure Signal.vi, niUSRPFetch Rx Data.vi, niUSRPAbort.vi and niUSRP Close Session.vi. Wherein niUSRP Open Rx session.vi receives the device name parameter as the corresponding transmitter vi and starts a transmission session between the USRP and the host for receiving the signal parameter and receiving the signal sample data. niUSRP Configure Signal.vi is to obtain corresponding IQ symbol rate, carrier frequency, antenna name for receiving and antenna gain parameters from the input control of the front panel and transmit these parameters to the USRP for configuring the receiving hardware. niUSRPFetch Rx data.vi receives the number of samples specified by the corresponding input control in a front panel and transmits a number of baseband symbols equal to this specified number from the USRP to the host. niusrpabort.vi is used to flush buffered data ready to receive the next data. niUSRP Close session.vi closes the session for data transfer between the USRP and the host and reports possible errors. Finally, the waveform chart module circularly displays the waveforms of the acquired IQ baseband signals of two paths each time.
The transceiver employs the following parameters. The parameters of the LFM signal of the transmitter are set to 2048 samples, the initial frequency is 1kHz, the end frequency is 2kHz, the sampling rate is 2 multiplied by 10 4 Hz, the frequency modulation slope is 19540.8Hz/s, the IQ symbol rate is 400k symbols/s, the carrier frequency is 915MHz, and the gain of the transmitting antenna is 20dB. The receiver parameter setting corresponds to the transmitter and the antenna gain is set to 20dB. The number of samples received at a time during the sampling test is 2048.
2. Data processing procedure
The received data is first processed by fractional Fourier transform, so that the influence caused by multipath effect can be effectively resisted. And (3) utilizing the focusing property of the fractional Fourier transform on the linear frequency modulation signal, obtaining a peak with good focusing property in the optimal fractional Fourier transform domain, and measuring the amplitude of the peak to obtain accurate receiving point position signal intensity information.
The actual received signal time domain waveform and its focusing result in the best fractional domain is shown in fig. 7. The focusing effect of the fractional fourier transform on the linear fm signal is evident from fig. 7. When the signal acquisition point is located in an area where multipath effects are strong, more than one focus spike will occur in the optimal fractional domain. And then, carrying out signal receiving intensity field reconstruction in the whole area by utilizing Gaussian process regression, thereby achieving the effect of reducing sampling points required for obtaining signal distribution. In order to visually compare the effect difference between the present scheme and the conventional scheme, a conventional median filtering process was used as a comparison. The result of the sampling node processing for reconstruction is shown in fig. 8. The processed data are input into a Gaussian process regression model for training, and a prediction result is obtained as shown in fig. 9.
Comparing the inner gate portions of fig. 9 a) and 9 b), it can be seen that the signal is deeply attenuated where no substantial attenuation should occur due to the presence of multipath effects, which is due to phase cancellation; the scheme based on fractional Fourier transform can effectively remove the influence of the points. Therefore, compared with a median filtering scheme, the scheme can play a good role in resisting multipath effect. In addition, due to the existence of the iron door, a large-area blind area appears due to the influence of shadow fading in the area behind the door, and the result of signal blind area reconstruction accords with an actual scene, so that the effectiveness of the scheme can be verified.
Claims (3)
1. The rapid acquisition method of the multi-band indoor signal distribution field is characterized by comprising the following steps of:
Step 1: an LFM signal source is arranged indoors;
Step 2: based on the LFM signal source in the step 1, performing drive test sampling by using receiving equipment;
Step 3: determining the position of a receiver based on the drive test sampling result in the step 2;
step 4: using the receiver for determining the position in the step 3 to perform signal processing and output of a measurement result;
Step 3 is specifically that in the process of determining the position of the receiver, a signal source is started, a receiving device moves, and a linear frequency modulation signal is received at the same time;
The position determining scheme comprises a pre-measured and calibrated sampling position recording scheme or ultra-wideband-based high-precision indoor positioning;
the step 4 specifically comprises the following steps,
Step 4.1: preprocessing a signal received by a receiver;
Step 4.2: performing interpolation recovery of a signal receiving intensity field on the preprocessed signal;
Step 4.1, the focusing of the LFM signal is performed by using fractional Fourier transform,
Step 4.1.1: for received signalsCarrying out energy focusing in the corresponding optimal fractional Fourier transform domain;
step 4.1.2: collecting the energy of each multipath peak of energy focusing and searching and superposing;
step 4.1.3: taking the superposition value in the step 4.1.2 as the received signal energy value of the current position;
The process of positioning the focusing peak in the optimal fractional Fourier transform domain in the step 4.1.1 is specifically that a focusing peak searching method is adopted, wherein the focusing peak searching method comprises a data size comparison method about a peak value and a zero crossing counting method for binarizing at a given threshold value;
The peak obtained through searching is converted into a time domain amplitude according to the conversion relation between the time domain and the fractional domain:
Wherein v max is the coordinate position of the peak value in the LFM signal transformation in the optimal fractional domain, The magnitude of the peak in the fractional domain; n is the number of signal sampling data points, sin () represents a sine function; a is the time domain amplitude value corresponding to the fractional domain peak value; p max is the optimal fractional Fourier transform order corresponding to the transmitted LFM signal;
Frequency modulation slope of p max and LFM signals The relation between the two is:
Wherein f 1 is the initial frequency at which the signal source can continuously transmit, and f 2 is the termination frequency at which the signal source can continuously transmit; t is the pulse period; cot () is a cotangent function;
Superposing the time domain amplitude of each peak value as a current signal receiving intensity value s x, and storing the value and the position into a two-dimensional tuple (x, s x) for storage;
the interpolation recovery process of step 4.2 is specifically that the sampled data of all the sampling points are sequentially arranged and expressed as (x|y):
For the unknown point position X *, the predicted result mean μ (y *|X*, X, y) of the signal reception intensity value y * thereof is obtained by the following equation:
Where k (X *, X) is the result of the calculation of the kernel function employed at positions X * and X, Is the observation noise of the environment, I is the identity matrix, () -1 is the inversion operation of the matrix;
The uncertainty of the prediction is expressed by the variance σ 2(y*|X*, X, y) of the prediction result:
2. The method for rapidly acquiring the distribution field of the multi-band indoor signal according to claim 1, wherein the step 1 is specifically that the LFM signal source is composed of a radio frequency device for transmitting a chirp signal and a control upper computer; the signal source can continuously send the linear frequency modulation signal with the initial frequency of f 1 and the ending frequency of f 2, and the mathematical expression of the LFM signal is as follows:
where Re { } represents the real part and T is the pulse period.
3. The method for rapidly acquiring the distribution field of the multi-band indoor signal according to claim 1, wherein the step 2 is characterized in that the receiving device comprises a receiver for receiving the radio frequency signal and an upper computer for storing the received signal; during reception, the device samples the received signal for at least more than one pulse period TThe information is sent to an upper computer for storage, the upper computer records the coordinate information x of the current position when storing, and the information x and the received signal of the current position are combined into a two-dimensional tuple/>Stored in a database.
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