September, 2005 Doc: IEEE 15-05-0524-00-004a Qi, Li, Umeda, Hara and Kohno (NICT) SlideTG4a1...
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Transcript of September, 2005 Doc: IEEE 15-05-0524-00-004a Qi, Li, Umeda, Hara and Kohno (NICT) SlideTG4a1...
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 1
Project: IEEE P802.15 Working Group for Wireless Personal Area Networks Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)(WPANs)
Submission Title: [Three ranging-related schemes]Date Submitted: [September, 2005]Source: [Yihong Qi, Huan-Bang Li, Masataka Umeda, Shinsuke Hara and Ryuji Kohno,
Company: National Institute of Information and Communications Technology ]Contact: Yihong Qi Voice:+81 46 847 5092, E-Mail: [email protected]]Abstract: [Three ranging-related schemes are presented: 1. for the problem that the first
arriving signals are often weak and NLOS, positioning using mulitpath delays will improve the accuracy. 2. a reduced dimensional approach is proposed for the bad GDOP problem. 3. a coherent delay estimation scheme is devised which works well with low sampling rate and feasible ADC implementation.]
Purpose: [to discuss three ranging-related schemes ]Notice: This document has been prepared to assist the IEEE P802.15. It is offered
as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein.
Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P802.15.
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 2
Outline Positioning using multipath delays (cf. first arrival
detection) Positioning in an ill-conditioned geometry (bad
GDOP (geometric dilution of precision)) A coherent delay estimation scheme with low
sampling rate Conclusions
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 3
Two Positioning Schemes
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 4
Current/conventional schemes
Ranging: first arrival detection
Positioning: based on multiple range estimates triangulation weighted least square (LS) methods
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 5
What are problems with the current schemes?
Positioning accuracy will be degraded due to
Weak first arriving signals, e.g., 6dB lower than the strongest path.
NLOS first arriving signals Bad GDOP (geometric dilution of precision)
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 6
Positioning using multipath delays
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 7
Motivation
The second and later arriving signals also carry information on the position of interest. cf. weak and/or NLOS first arriving signals
Positioning using both Multipath delays Their statistic information (e.g., mean,
variance)
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 8
Two numerical examples based on analytical results
For illustration purpose, some simplifying assumptions on multipath delays:
Exponential or equal gain models The minimum delay resolution being the inverse
of chip duration Gaussian NLOS delay variables
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 9
Numerical example 1
Positioning accuracy vs. num of multipath
Equal gain
Exponential gain with -6dB
Exponential gain with -3dB
Observation: use of more strong multipaths can improve the positioning accuracy
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 10
Numerical example 2
For a fair comparison:
Using• fixed total energy;• relative accuracy
improvement, compared with the conventional method using only the first arrivals
Three types of system channels
1
2
3
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 11
Numerical example 2 (cont’d)
relative accuracy improvement vs. standard deviation of NLOS delays
Observation: using more multipaths is especially effective for accuracy improvement in wideband systems
1MHz
100MHz
5MHz
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 12
A reduced-dimensional method for bad GDOP (geometric dilution
of precision) cases
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 13
What is the bad GDOP?
Good GDOP case: nodes are distributed evenly
a2
a3
a1
p
Mobile node
a2a3a1
p
Mobile node
Bad GDOP case: all nodes are lined up
The error is small.
The error is large.
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 14
What is the problem?
a2
a3
a1
p
m
Bad dim: x Good dim: y
Two dimensional positioning
estimation (x,y) vs.
an essentially one-dimensional
problem (y axis only)
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 15
A reduced dimension approach
1. Find the good dim(s)
2. Perform a regular positioning in the good dimension
3. Estimate the coordinate in the bad dim(s) separately
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 16
A simulation result for 2-D bad GDOP
Conventional method
Reduced dimensional method
Theoretical limit
Positioning accuracy vs. standard deviation of ranging errors
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 17
Flashback
Positioning using multipath delays For the problem of weak and/or NLOS first
arriving signals Con: increased computation complexity
A reduced-dimensional approach for positioning For bad GDOP geometry
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 18
Coherent delay estimation with low sampling rate and feasible ADC
implementation
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 19
Correlator A/D
Delay estimation/First-arrival detection
A delay estimate
)(tr
)(tsA transmit signal
A basic system model
)(tc
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 20
Two ways of implementing ADC
LO
LPF
LPF
code-correlator
code-correlator
BPF
π/2
ADC
ADC
outputMatched toGaussian pulse
Spreadingcode
Difficult to implement
easy to implement
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 21
What is the problem?
tm+1tn
h(tn)
h(tm)
h(tm+1)
h(tm+Z-1)
tm+2 tm+Z
Given samples of a correlation function, how to estimate the time instant corresponding to the peak?
?̂correlation function
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 22
What is information we know?
tm+1tn
tm+2 tm+Z
correlation
autocorrelation
correlation = autocorrelation of s(t) +noise
The expression is known. Statistics is known.
correlation function
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 23
A natural way to use all information
Formulate maximum likelihood estimation (ML).
However, it is complicated: One dimension iterative searching Nonlinear autocorrelation function involved Lots of samples (N) involved
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 24
Our approach: simplified MLE
tm+1 tn
h(tn)
h(tm)
h(tm+1)
h(tm+Z-1)
tm+2 tm+Z
Intuition: samples near the peak are more important.
• Use less samples
• Taylor expansion of autocorrelation function around the peak
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 25
A simple solution
,)(1
)(ˆ
333
333
thW
thWt
T
T
.function ation autocorrel theis )( ,
)0()()2(
)()0()(
)2()()0(
samples ,))()()(()(
instants; time,)(
1
3
213
213
g
gTgTg
TggTg
TgTgg
tctctc
tttT
mmm
Tmmm
W
tc
t
where
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 26
A simple solution
• An algebraic solution, no iterative search• Less than 4 samples in general• No nonlinear function any more• Independent of noise level • Optimal in the sense that the estimate is approaching to the theoretical lower limit as over-sampling is sufficiently large.
,)(1
)(ˆ
333
333
thW
thWt
T
T
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 27
Simulation parameters
• PRF=30.875MHz• Sampling rate fs (ADC)=494MHz (=16xPRF)• Ternary sequence with length of 31• Gaussian Pulse with bandwidth 500MHz• AWGN Channel
Conventional method: Pick up the largest sampleInterpolation method: Not include the autocorrelation info. .
)(1
)(ˆ
33
33
th
tht
T
T
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 28
Simulation result 1R
MS
Est
imat
ion
Err
or [
nsec
]
Eb/N0 [dB]
ADC after Code Correlator
ADC before Code Correlator Conventional method
Simplified ML
Interpolation
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 29
Simulation result 2
Eb/N0=-3dB
Conventional method
Interpolation
Simplified ML
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 30
Advantages Working well at low sampling rate (less than signal
bandwidth) Feasible ADC implementation Low computation complexity
Same level of complexity compared with conventional schemes Independent of noise level
Ongoing work: incorporating decay patterns for multipath scenarios
TG4a
September, 2005 Doc: IEEE 15-05-0524-00-004a
Qi, Li, Umeda, Hara and Kohno (NICT) Slide 31
Conclusions
Positioning using multipath delays A reduced dimensional approach for
positioning in bad GDOP A coherent delay estimation scheme with
low sampling rate and feasible ADC implemetation