alexander gavrilov, cmst
DESCRIPTION
Long-range acoustic transmissions for navigation, communication, and ocean observation in the Arctic. Alexander Gavrilov, CMST. Peter Mikhalevsky, SAIC. OUTLINE. Some examples of long-range acoustic transmissions in the Arctic Ocean (TAP and ACOUS experiments) - PowerPoint PPT PresentationTRANSCRIPT
Long-range acoustic transmissions Long-range acoustic transmissions
for navigation, communication, and for navigation, communication, and
ocean observation in the Arcticocean observation in the Arctic
Alexander Gavrilov, CMST
Peter Mikhalevsky, SAIC
OUTLINE
1. Some examples of long-range acoustic transmissions in the Arctic Ocean (TAP and ACOUS experiments)
2. Numerical prediction of transmission loss at different frequencies and experimental results
3. Possible outline of the network• Navigation• Communication• Ocean Observation
4. Problems ?
TAP (blue) and ACOUS (red) experiment paths in the Arctic Ocean
APLIS
ACOUSSource
Nanse
n Bas
in
Fram
Bas
in
Greenland
RussiaCanada
Spitsbergen
1805 1810 1815 1820 1825 1830 1835
500
1000
1500
2000
2500
3000
3500
Travel time, s
Am
plitu
de,
Pa
3
2
4
1
- numerical prediction
TAP signal at ice camp SIMI after pulse compression
Evidence of multi-path (multi-mode) propagation
4500 50 100 150 200 250 300 350 40060
65
70
75
80
85
90
95
100
105
110
Day number
Sign
al le
vel,
dB re
. 1
Pa
Before processing
ACOUS signal and noise levels at individual receivers of the Lincoln Sea array
0 50 100 150 200 250 300 350 400 45050
60
70
80
90
100
110
120
Day number
Sign
al le
vel,
dB re
. 1
Pa
After pulse compression
Noise level in a 1-Hz frequency band
(ACOUS source level: 195 dB; distance: ~ 1250 km)
Noise level limited by receivers’ dynamic range
0 50 100 150 200 250 300 350 400 450-5
0
5
10
15
20
25
30
35
40
45
Day number
SN
R, d
B
SNR before (blue) and after (red) pulse compression
Cross-correlation matrix of 10 periods of ACOUS signal
2 4 6 8 10
1
2
3
4
5
6
7
8
9
100.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
1 3 5 7 9Period number
SNR and coherence of ACOUS signals onthe Lincoln Sea array
Exceptional temporal stability of the channel at 20 Hz!
100 200 300 400 500 600 70035
40
45
50
55
60
65
70
75
80
Depth, m
Sig
nal l
evel
, dB
re. 1
P
a
Level of two ACOUS signals (blue) and noise (red) on APLIS vertical array after pulse compression
(Distance: ~2720 km)
~ 34 dB theoretical limit
Variation of ambient noise level in the Arctic
101
102
10365
70
75
80
85
90
95
100
105
Frequency, Hz
Noi
se le
vel,
dB re
. 1
Pa/
Hz1/
2
~90% of time
10 1
10 2
10 -3
10 -2
10 -1
10 0
Frequency, Hz
Atte
nuat
ion,
dB
/km
F 1.5
Ice model parameters: mean ice thickness – 3.5 m; bottom standard deviation – 2.3 m; top standard deviation – 0.6 m; correlation length – 40 m
Frequency dependence of modes 1 - 40 attenuation modeled for the Central Arctic Basin and some experimental results
NUSC 1959
FRAM IV, 1982
TAP, 1994 (mode 1)
TAP, 1994 (modes 2-4)
ACOUS, APLIS (mode 1)
ACOUS, APLIS (mode 2)
Transmission loss along ACOUS path at 50 m and 400 m modeled for a broadband signal
0-dB SNR for a 50-Watt (~190 dB) source
Range, km200 400 600 800 1000 1200
30
40
50
60
70
80Depth: 400 m
-120
-115
-110
-100-95
-90
-140
-130
-120
-110
-100
-90
-80
-105
200 400 600 800 1000 1200
30
40
50
60
70
80-135
-130-125
-120
-115
-110
-105-100
-95
-90
-85
Range, km
Freq
uenc
y, H
z
Depth: 50 m
-20-dB SNR for a 50-Watt (~190 dB) source
Cabled/autonomous transceiver nodes
Cabled transceiver nodeswith shore terminals
Autonomous sources Acoustic observation pathsCable
90E
30
150
60
120
120
60
150
30
1800
GGGrrreeeeeennnlllaaannnddd
RRRuuussssssiiiaaa
CCCaaannnaaadddaaa
4000
500
35002000
500
500
2000
3500
2000
500
ACOUSsource
90WNotional acoustic network
1. Navigation:• Stationary acoustic sources are to transmit pulse-like signals
for accurate measurements of travel times to moving platforms. Nav. signals should also contain certain information (at least source ID numbers, UTC time, etc.).
3. Observation (thermometry, ice monitoring)Feasible for stationary receivers/transceivers. For mobile platforms, it requires accurate timing and complicated interpretation of travel time data.
2. Communication:• Two-way communication is needed to check the operational
state (most important) and to track position of mobile platforms
• Underwater communication of oceanographic data over long distances does seem feasible
) (),()( mss , t-kTS, t-iTS=tX dcc
))21(exp()(2)(1
0o
N-
i=isss c- jt-iTE = t, S c
c{ }c , c , ..., cN-0 1 1
dm m mN-m d , d , ..., d { }0 1 1
A simple method to design navigational/ communicational/observational signals
Series of two signals: training (observational) signals followed by informational signal = navigational signal
is the M-sequence of length N = 2M - 1
, where
, and
is the Hadamard code of number m < N
l
j=
M
i=
mijij
lm Syhy0 0
*0
)( Re=)(
Processing: compute the likelihood function:
for each message m, using Hadamard transform
Signal-to-noise ratio
10-1
1.0
0.0 0.05 0.10
0.15 0.20 0.25
M=512
M=1024
10-2
10-3
E
rror
pro
babi
lity
Error probability for binary message m at different SNR for two different signal bases
1. Weight, power consumption and reliability of low-frequency sources, especially for mobile platforms
Most serious problems
3. Slow communication rate
2. Doppler effect for mobile platforms
4. Accurate timing for mobile platforms
5. Separation of acoustic thermometry/halinometry data from navigational errors.
6,7,… ?