CN115329276B - PDOA estimation and on-chip data fusion method based on multiple antennas - Google Patents

PDOA estimation and on-chip data fusion method based on multiple antennas Download PDF

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CN115329276B
CN115329276B CN202210949855.3A CN202210949855A CN115329276B CN 115329276 B CN115329276 B CN 115329276B CN 202210949855 A CN202210949855 A CN 202210949855A CN 115329276 B CN115329276 B CN 115329276B
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杨旭磊
张强
黄先日
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Shanghai Keruixin Microelectronics Co ltd
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Abstract

The invention discloses a PDOA estimation and on-chip data fusion method based on multiple antennas, which comprises the steps of carrying out cross-correlation calculation on ADC data corresponding to each antenna and a local sequence respectively; first path detection, extracting a cross-correlation result of each path by taking the length of a symbol as a period according to the result of the detection output of the first path; the extracted cross-correlation result of each branch is respectively and conjugate multiplied with the cross-correlation result of the main path, and the corresponding phase difference is solved; meanwhile, each shunt phase difference is compensated by utilizing the updated phase difference; performing time delay compensation on each piece of shunt data; superposing and normalizing the compensated data to obtain combined data; after the PDOA estimation enabling signal is pulled down, the PDOA result is locked, and the PDOA is calculated by using the phase difference after locking and the delay value of the antenna. The multi-antenna data is processed in the chip, the influence of carrier frequency offset and sampling frequency offset on the PDOA estimation result is eliminated, the estimation accuracy of the PDOA is greatly improved, the secondary path data is corrected by using the estimation result of the phase difference and the corresponding delay, and the corrected secondary path data and the main path data are combined to form one path of data, so that the complexity of baseband processing is reduced.

Description

PDOA estimation and on-chip data fusion method based on multiple antennas
Technical Field
The invention relates to the technical field of Ultra-wide band (UWB) communication positioning, in particular to a PDOA estimation and on-chip data fusion method based on multiple antennas.
Background
At present, an outdoor positioning technology based on GNSS is relatively mature, but in the indoor, satellite signals are easily shielded, normal positioning service cannot be completed, and positioning accuracy cannot meet service requirements. In recent years, the demand for high-precision positioning services is increasing, and 70% -80% of activities of people are indoors according to statistics, so that the development of indoor positioning technology has ten important meanings. Based on various requirements, many corresponding positioning technologies have been developed and achieve good results, such as infrared, radio frequency identification, ultrasound, WIFI, bluetooth, zigbee, visual positioning, and the like. However, the curves of the indoor positioning sensing system are low in positioning accuracy or strict in requirements on the environment, and the requirements of people on high accuracy and good environmental adaptation of the indoor positioning sensing system cannot be met. Compared with other wireless positioning technologies, the UWB has the advantages of strong interference resistance, extremely wide bandwidth, high transmission rate, low power consumption and the like. The (Angle of Arrival, AOA) positioning based on the signal Arrival Angle has been the focus of research because of few required base stations, no requirement for high-precision system clocks, small calculation amount and strong real-time performance. The AOA needs to be obtained by calculating an arrival phase difference (Phase Difference of Arrival, PDOA), however, the calculation of the PDOA needs to be obtained by calculating two or more antennas, for a multi-antenna group formed by a single antenna chip, the calculation of the PDOA needs to be processed off-chip, is easily affected by carrier frequency offset and sampling frequency offset, and for a multi-antenna chip, the calculation of the PDOA can be processed on-chip, and the performance of the multi-antenna group is higher than that of a multi-antenna group formed by a single antenna chip. For the multi-antenna chip, the multi-antenna data processing problem is faced, if the multi-antenna data is processed in parallel, the complexity of the baseband is greatly increased, so how to utilize the PDOA calculation gain brought by the multi-antenna and meanwhile, the data fusion of the multi-antenna needs to be considered is an important point of research.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a PDOA estimation and on-chip data fusion method based on multiple antennas.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a multi-antenna based PDOA estimation and on-chip data fusion method, the method comprising the steps of:
step 1, performing cross correlation calculation on ADC data corresponding to each antenna and a local sequence respectively;
step 2, first path detection, and extracting a cross-correlation result of each path by taking the length of a symbol as a period according to the result output by the first path detection;
step 3, the cross-correlation result of each branch is respectively multiplied by the cross-correlation result of the main path in a conjugate way, and the phase is obtained according to the result of the conjugate multiplication, so that the phase difference of each branch relative to the main path is obtained;
step 4, the phase difference calculated by each symbol is corrected and updated by a Kalman filtering method by taking the symbol length as a period;
step 5, compensating the phase difference between the opposite main paths of each shunt by using the updated phase difference;
step 6, calculating the sampling time delay of each branch relative to the main path by using the updated phase difference, and performing time delay compensation on each branch data;
step 7, superposing and normalizing the compensated data to obtain combined data;
and 8, after the PDOA estimation enabling signal is pulled down, locking a PDOA result, and calculating the PDOA by using the phase difference after locking and the delay value of the antenna.
In the step 4, the phase difference calculated by each symbol is corrected and updated by the kalman filtering method with the symbol length as the period, and the correction and updating method is as follows:
Figure SMS_1
wherein ,
Figure SMS_2
for the updated result of the mth symbol, < +.>
Figure SMS_3
Estimated result of the m+1th symbol, < >>
Figure SMS_4
K is the updated result of the (m+1) th symbol G (m+1) is the gain coefficient of the (m+1) th symbol.
In the step 6, the sampling delay of each branch relative to the main path is calculated by using the updated phase difference:
Figure SMS_5
wherein ,
Figure SMS_6
is the phase difference of the mth symbol of the Sn shunt antenna relative to the main antenna, f c For carrier frequency, delta t is determined according to the relative delay of the master antenna and the slave antenna Sn The estimation result of (m) should be within a range (-1/(2 f) c )+(t Sn -t M )<Δt Sn (m)<1/ (2f c )+(t Sn -t M ) If not within the preset range, it is necessary to add or subtract 1/f c Will be deltat Sn (m) adjusting to a preset range, wherein t Sn For the antenna delay corresponding to the Sn shunt antenna, t M And the delay is the antenna delay corresponding to the main path antenna.
In the step 6, the delay compensation is performed on each piece of shunt data, and the method comprises the following steps:
first by a time difference deltat Sn (m) and (t) Sn -t M ) In contrast, whether the shunt leads or lags the main circuit is judged, and for the shunt data leading the main circuit data, the compensation method is as follows:
Figure SMS_7
wherein ,Δts For sampling interval time, N is the nth sampling point in one symbol, N represents the sampling point number of one symbol, s' n (t) is the data after phase compensation of the Sn shunt antenna at the time t, delta t Sn For the delay of Sn shunt antenna data relative to main path data s Sn (t) is data at time t after delay compensation;
for shunt data lagging the main way data, the compensation method is as follows:
Figure SMS_8
in the step 7, the compensated data is overlapped and normalized to obtain the combined data, and the method comprises the following steps:
Figure SMS_9
wherein sM (n) is data corresponding to the main path antenna, w 0 Is the weight coefficient of the main antenna, s Si (n)～s″ Sn (t) is the data corresponding to each branch antenna, w 1 ～w n The weight coefficient corresponding to each branch antenna is used;
in the step 8, the PDOA is calculated by using the phase difference after locking and the delay value of the antenna, and the method is as follows:
Figure SMS_10
wherein
Figure SMS_11
In the range of-pi to pi, if +.>
Figure SMS_12
If it is
Figure SMS_13
The invention has the beneficial effects that:
1. the data of multiple antennas are processed in a chip, so that the influence of carrier frequency offset and sampling frequency offset on the PDOA estimation result is eliminated, and the estimation accuracy of the PDOA is greatly improved;
2. the estimation result of the phase difference and the corresponding delay are utilized to correct the secondary path data, and then the corrected secondary path data and the corrected primary path data are combined into one path of data, so that the complexity of baseband processing is reduced;
3. the signal to noise ratio of the first path signal can be effectively improved by the data merging method, so that the pulse waveform of the first path signal can be recovered more accurately, and the time resolution of the first path signal is improved.
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FIG. 1 is a system Jian Lvetu of the multi-antenna based PDOA estimation and on-chip data fusion method of the invention;
FIG. 2 is a schematic diagram of a system architecture of a multi-antenna based PDOA estimation and on-chip data fusion method according to the present invention;
FIG. 3 is a system processing flow diagram of a multi-antenna based PDOA estimation and on-chip data fusion method of the invention;
FIG. 4 is a schematic diagram of a data flow of first path detection based on a multi-antenna PDOA estimation and on-chip data fusion method according to the present invention;
FIG. 5 is a flow chart of a process for detecting the first path of the PDOA estimation and on-chip data fusion method based on multiple antennas;
fig. 6 is a process flow diagram of a head path search method based on a multi-antenna PDOA estimation and on-chip data fusion method according to the present invention.
Detailed Description
The following description of the present invention will further illustrate the present invention, and the following examples are provided on the premise of the present technical solution, and the detailed implementation and the specific operation procedure are given, but the protection scope of the present invention is not limited to the present examples.
It should be noted that, as shown in fig. 1, for multiple antennas, one antenna is defined as a master antenna, such as antenna 101, and the other antennas are defined as slave antennas, such as antenna 102 and antenna 103. The data path corresponding to the master antenna is a master path, and the data path corresponding to the slave antenna is a slave path. The main path is used as a reference when PDOA estimation and data combination are carried out.
The invention relates to a PDOA estimation and on-chip data fusion method based on multiple antennas, which comprises the following steps:
step 1, performing cross correlation calculation on ADC data corresponding to each antenna and a local sequence respectively;
step 2, first path detection, and extracting a cross-correlation result of each path by taking the length of a symbol as a period according to the result output by the first path detection;
step 3, the cross-correlation result of each branch is respectively multiplied by the cross-correlation result of the main path in a conjugate way, and the phase is obtained according to the result of the conjugate multiplication, so that the phase difference of each branch relative to the main path is obtained;
step 4, the phase difference calculated by each symbol is corrected and updated by a Kalman filtering method by taking the symbol length as a period;
step 5, compensating the phase difference between the opposite main paths of each shunt by using the updated phase difference;
step 6, calculating the sampling time delay of each branch relative to the main path by using the updated phase difference, and performing time delay compensation on each branch data;
step 7, superposing and normalizing the compensated data to obtain combined data;
and 8, after the PDOA estimation enabling signal is pulled down, locking a PDOA result, and calculating the PDOA by using the phase difference after locking and the delay value of the antenna.
Example 1
As shown in fig. 2, the processing flow in this embodiment is as follows: the data received by the three antennas are respectively subjected to data acquisition through respective ADC, the acquired data are respectively subjected to cross-correlation calculation with local sequences, the calculated phase difference is calculated according to the calculation result of the cross-correlation extracted by the first path index, the calculated phase difference is tracked and corrected in a Kalman filtering mode, the phase compensation is respectively carried out on the data of two secondary paths according to the corrected phase difference, meanwhile, the time difference of the time delay of the data of the secondary paths is calculated according to the phase difference, the time is corrected according to the value range of the time difference, the time delay compensation is carried out on the data of the two secondary paths according to the corrected time difference, the data combination is carried out on the data of the two secondary paths after compensation and the data of the main path (alignment is realized through a time delay module, and finally, the combined data is normalized and is output to the baseband module. When the PDOA calculation module is enabled, the phase difference PDOA1 and PDOA2 of the two secondary paths relative to the main path are calculated by utilizing the phase difference after tracking and correcting and considering the antenna delay difference and the value range.
As shown in fig. 3, the process flow of each step in this embodiment includes 8 steps, and the process of each step is specifically described below with reference to fig. 2 and 3:
s301: the ADC data corresponding to each antenna are respectively subjected to correlation calculation with the local sequence;
taking a main path antenna as an example, the cross-correlation calculation method is as follows:
Figure SMS_14
where N is the number of sampling points of one symbol, s M (tau) is the ADC sampled signal, l (tau-n) is the local signal, r M (n+N) is the result after the cross-correlation.
S302: first path detection, extracting a cross-correlation result of each path by taking symbol length as a period according to a result (index) output by the first path detection;
the first path detection process is shown in fig. 4, the specific process flow is shown in fig. 5, and the specific steps are as follows in combination with fig. 3 and fig. 4:
s501: conjugate multiplication is carried out on the cross-correlation results of the master-slave paths;
the main-path cross-correlation calculation module 201 outputs the result r M (n) output result r from the way cross-correlation calculation module 202 S1 The conjugate multiplication method (n) is as follows:
r MS1 (n)＝r S1 (n)*conj(r M (n))；
wherein conj () is a conjugate operation;
the main-path cross-correlation calculation module 201 outputs the result r M (n) output from the road cross-correlation calculation module 203Results r S2 The conjugate multiplication method (n) is as follows:
r MS2 (n)＝r S2 (n)*conj(r M (n))；
s502: accumulating the result after conjugate multiplication by taking the symbol length as a period;
the accumulating module 403, the method of the accumulating process is as follows:
r cum1 (n)＝(1-ω G )*r cum1 (n-N)+ω G *r MS1 (n)；
wherein ,ωG N is the number of sampling points in one symbol period, r cum1 (N-N) weighting the accumulated result at the same position of the symbol;
in this embodiment, the weight coefficient takes the value of: 1,1/2, 1/4,1/8, …;
the accumulation module 404, the method of the accumulation process is as follows:
r cum2 (n)＝(1-ω G )*r cum2 (n-N)+ω G *r MS2 (n)；
s503: taking absolute values of the accumulated results, and summing and combining the multipath data;
the process method is as follows:
r cum (n)＝|r cum1 (n)|+|r cum2 (n)|；
s504: performing first-path detection by utilizing the combined data, and outputting a first-path index;
as shown in fig. 6, the specific processing steps of the process flow chart of the first path detection are as follows:
s601: solving dynamic threshold base according to the data after summation and combination
By accumulating the combined data r cum (n) starting sliding window calculation of dynamic threshold base number, wherein the calculation method is as follows:
Figure SMS_15
wherein, N is the sampling point number in one symbol period;
s602: the dynamic threshold is calculated according to the threshold base, and the calculation method is as follows:
D th (n)＝d th (n)*r coef ；
wherein ,Dth (n) is data r cum (n) corresponding dynamic threshold, r coef Converting the dynamic threshold base into a proportionality coefficient of a dynamic threshold;
s603: by combining data r cum (n) dynamic threshold D th (n) comparing, searching the rising edge of the head path forward, and detecting the position of the head path according to the rising edge;
when r is cum (n)＞D th (n) in order to detect the rising edge of the head path, starting the head path position detection;
if r cum (n+1)＞r cum (n)＞D th(n) and rcum (n+1)＞ r cum (n+2)＞D th (n+2), then r cum (n+1) is a value corresponding to the detected first-path index, fpidx= (n+1)% N is the first-path position in one symbol period, wherein% is the remainder operation;
s604: when the positions of the first paths detected by the three continuous symbols are the same, the first path index FpIdx is output.
S303: the extracted cross-correlation result of each branch is respectively multiplied by the cross-correlation result of the main path in a conjugate way, and the phase is obtained according to the result of the conjugate multiplication, so that the phase difference of each branch relative to the main path is obtained;
the extraction main-path cross-correlation module 201 outputs a result r according to the first-path index FpIDx M (fpidx+m x N) and outputting the result r from the way cross-correlation module 202 S1 (fpidx+m×n), the conjugate multiplication calculation method is as follows:
r′ MS1 (m)＝r S1 (FpIdx+m*N)*conj(r M (FpIdx+m*N))；
wherein m is the mth symbol after the first path is output;
also, based on the first path index FpIdx, the extract main-path cross-correlation module 201 outputs the result r M (fpidx+m x N) and outputting the result r from the way cross-correlation module 203 S2 (FpIdx+m* N) to obtain the result r 'after conjugate multiplication' MS2 (m)
Based on the conjugate multiplication result, the phase difference calculation module 204 obtains the phase difference of each branch with respect to the main path as follows:
Figure SMS_16
similarly, the phase difference calculation module 205 obtains the phase difference of each branch with respect to the main path as
Figure SMS_17
S304: the phase difference calculated by each symbol is corrected and updated by a Kalman filtering method by taking the symbol length as a period;
the method in the phase difference tracking and correction module 206 is as follows:
Figure SMS_18
wherein ,
Figure SMS_19
for the updated result of the mth symbol, < +.>
Figure SMS_20
Estimated result of the m+1th symbol, < >>
Figure SMS_21
K is the updated result of the (m+1) th symbol G (m+1) is the gain factor of the (m+1) th symbol;
also, the phase difference tracking and correcting module 207 may output a result expressed as
Figure SMS_22
S305: meanwhile, the phase difference between each shunt and the corresponding main circuit is compensated by utilizing the updated phase difference;
the result of the data from way 1 after being compensated by the phase compensation module 210 is:
Figure SMS_23
similarly, the result of the data from way 2 after being compensated by the phase compensation module 211 is s' S2 (n)
S306: calculating the sampling time delay of each branch relative to the main path by using the updated phase difference, and performing time delay compensation on each branch data;
the output result calculation method of the phase difference to time difference module 212 is as follows:
Figure SMS_24
wherein ,
Figure SMS_25
is the phase difference of the mth symbol of the S1 branch antenna relative to the main antenna, f c Is the carrier frequency;
it is also available that the output result of the phase difference to time difference module 213 from the data of way 2 is Δt S2 (m)；
According to different relative delays of the master antenna and the slave antenna, the output result of the phase difference-to-time difference module is required to be corrected;
assume that the antenna delay of the main path antenna is t M The antenna delay of the slave path 1 antenna is t S1 The antenna delay of the secondary path 2 antenna is t S2 ；
Deltat S1(m) and ΔtS2 (m) ranges from (-1/(2 f), respectively c )+(t S1 - t M )＜Δt S2 (m)＜1/(2f c )+(t S1 -t M ) Sum (-1/(2 f) c )+(t S2 - t M )＜Δt S2 (m)＜1/(2f c )+(t S2 -t M ))；
For Δt S1(m) and ΔtS2 (m) out of range, requiring plus or minus 1/f c Will be deltat S1(m) and ΔtS2 (m) adjusting to be within a set range;
using calculated Δt S1(m) and ΔtS2 (m) compensating the corresponding sub-path data by delta t S1 (m) compensation explanation is given as an example;
first by a time difference deltat S1 (m) and (t) S1 -t M ) In contrast, it is determined whether the shunt is leading or lagging with respect to the main path:
Δt S1 (m)＜(t S1 -t M ) Indicating that the shunt data is ahead of the main data, the compensation method is as follows:
Figure SMS_26
wherein ,Δts Is the sampling interval time;
Δt S1 (m)＞(t S1 -t M ) Indicating that the shunt data lags the main data, the compensation method is as follows:
Figure SMS_27
the same method can obtain the value s' after delay compensation from the road 2 S2 (n)
S307: superposing and normalizing the compensated data to obtain combined data;
the method comprises the following steps:
Figure SMS_28
wherein ,w0 Weight coefficient w for main path antenna data 1 and w2 Respectively, slave path antenna data s S1(n) and s″S2 (n) corresponding weight coefficients;
s308: after the PDOA estimation enabling signal is pulled down, the PDOA result is locked, and the PDOA is calculated by using the phase difference after locking and the delay value of the antenna;
taking the slave way 1 as an example, use is made of
Figure SMS_29
The method for calculating the PDOA of the master antenna 101 and the slave antenna 102 by the PDOA calculation module 208 is as follows:
Figure SMS_30
wherein
Figure SMS_31
In the range of-N to pi, if +.>
Figure SMS_32
Figure SMS_33
If it is
Figure SMS_34
The same method uses
Figure SMS_35
The PDOA of the master antenna 101 and the slave antenna 103 is calculated as +.>
Figure SMS_36
Various modifications and variations of the present invention will be apparent to those skilled in the art in light of the foregoing teachings and are intended to be included within the scope of the following claims.

Claims (1)

1. A multi-antenna based PDOA estimation and on-chip data fusion method, the method comprising the steps of:
step 1, performing cross-correlation calculation on ADC data corresponding to each antenna and a local sequence respectively;
step 2, first path detection, and extracting a cross-correlation result of each path by taking the symbol length as a period according to the result output by the first path detection;
step 3, the cross-correlation result of each branch is respectively multiplied by the cross-correlation result of the main path in a conjugate way, and the phase is obtained according to the result of the conjugate multiplication, so that the phase difference of each branch relative to the main path is obtained;
step 4, the phase difference calculated by each symbol is corrected and updated by a Kalman filtering method by taking the symbol length as a period;
step 5, compensating the phase difference between the opposite main paths of each shunt by using the updated phase difference;
step 6, calculating the sampling time delay of each branch relative to the main path by using the updated phase difference, and performing time delay compensation on each branch data;
step 7, superposing and normalizing the compensated data to obtain combined data;
step 8, after the PDOA estimation enabling signal is pulled down, the PDOA result is locked, and the PDOA is calculated by using the phase difference after locking and the delay value of the antenna, wherein in step 4, the phase difference calculated by each symbol is corrected and updated by a kalman filtering method with the symbol length as a period, and the correction and update method is as follows:
Figure QLYQS_11
wherein ,
Figure QLYQS_2
is->
Figure QLYQS_6
Updated result of each symbol,/->
Figure QLYQS_3
First->
Figure QLYQS_5
Figure QLYQS_12
Estimation of individual symbolsCounting result (s)/(s)>
Figure QLYQS_15
Is->
Figure QLYQS_10
Updated result of each symbol,/->
Figure QLYQS_16
Is->
Figure QLYQS_1
In the step 6, the sampling delay of each branch relative to the main path is calculated by using the updated phase difference: />
Figure QLYQS_8
wherein ,/>
Figure QLYQS_13
Is->
Figure QLYQS_17
First part of shunt antenna>
Figure QLYQS_18
Phase difference of the individual symbols with respect to the main antenna, < >>
Figure QLYQS_21
For carrier frequency, according to the relative delay of the master antenna and the slave antenna, the method is characterized in that +.>
Figure QLYQS_19
Is within a range +.>
Figure QLYQS_23
Figure QLYQS_20
If not within the preset range, it is necessary to add or subtract +.>
Figure QLYQS_22
Will->
Figure QLYQS_4
Is adjusted to be within a preset range, wherein->
Figure QLYQS_7
Is->
Figure QLYQS_9
Antenna delay corresponding to shunt antenna, < >>
Figure QLYQS_14
In the step 6, delay compensation is performed on each piece of shunt data for the antenna delay corresponding to the main path antenna, and the method comprises the following steps:
first by time difference
Figure QLYQS_25
And->
Figure QLYQS_29
In contrast, whether the shunt leads or lags the main circuit is judged, and for the shunt data leading the main circuit data, the compensation method is as follows: />
Figure QLYQS_34
wherein ,
Figure QLYQS_27
for sampling interval time, +.>
Figure QLYQS_31
Is +.>
Figure QLYQS_36
Sampling points->
Figure QLYQS_37
Sample points representing a symbolThe number of the product is the number,
Figure QLYQS_24
is->
Figure QLYQS_28
Shunt antenna is +.>
Figure QLYQS_32
Time-of-day phase-compensated data, +.>
Figure QLYQS_33
Is->
Figure QLYQS_26
Delay of shunt antenna data relative to main data, < >>
Figure QLYQS_30
For compensating delay>
Figure QLYQS_35
Time of day data;
for shunt data lagging the main way data, the compensation method is as follows:
Figure QLYQS_38
in the step 7, the compensated data is overlapped and normalized to obtain the combined data, and the method comprises the following steps:
Figure QLYQS_39
wherein />
Figure QLYQS_40
Is the data corresponding to the main path antenna,
Figure QLYQS_41
weight coefficient of main path antenna, +.>
Figure QLYQS_42
For each partData corresponding to the road antenna, ">
Figure QLYQS_43
The weight coefficient corresponding to each branch antenna is used;
in the step 8, the PDOA is calculated by using the phase difference after locking and the delay value of the antenna, and the method is as follows:
Figure QLYQS_44
wherein />
Figure QLYQS_45
Is in the range of
Figure QLYQS_46
If->
Figure QLYQS_47
Figure QLYQS_48
If it is
Figure QLYQS_49
/>
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