Range estimation using multipath arrivals from 20 Hz fin whale vocalizations recorded in the NE Pacific Ocean
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1 Range estimation using multipath arrivals from 2 Hz fin whale vocalizations recorded in the NE Pacific Ocean S c h o o l o f O c e a n o g r a p h y Michelle Weirathmueller and William S.D. Wilcock University of Washington Funded by: U n i v e r s i t y o f W a s h i n g t o n DCLDE 215
2 Cascadia Initiative experiment and Neptune Canada cabled observatory
3 Keck Endeavour Network Keck Network Keck Seismometer NEPTUNE Canada Broadband Seismometer Cable Explorer Plate Nootka Fault Endeavour Endeavour 21- ODP ODP Barkley Canyon 29- Elevation, m W 129 W 128 W 127 W 126 W 125 W
4 Keck Endeavour Network 2 km Ocean bottom seismometer (OBS) dataset instruments Water depth ~ 22m
5 Keck experiment: Call tracking Network used to find 154 whale tracks during the first year of data collection Wilcock, William SD. JASA 132 (212): 248. Soule, Dax C., and William SD Wilcock. JASA 133 (213): 1751.
6 Neptune Canada Cascadia Basin Keck Network Keck Seismometer NEPTUNE Canada Broadband Seismometer Cable Explorer Plate Nootka Fault Endeavour Endeavour 21- ODP ODP Barkley Canyon 29- Elevation, m W 129 W 128 W 127 W 126 W 125 W
7 Point transect distance sampling We want: calls per unit area 5π 3π π OBS Estimate range from OBS to each detected call, fit model to range distribution to estimate call density
8 Sound speed Depth Multipath arrivals Amplitude Time
9 Store multipath structure near each pick Sample call time series: Band-pass filtered (15-35 Hz) Model call Time (seconds) Sample call: Cross-correlator output Time (seconds) Time series of received signal and model chirp basebanded at 2 Hz Cross-correlate basebanded signal and model chirp to find calls (including multipaths)
10 Modeling multipath timing and amplitude Time delay (seconds) Direct MP1 MP2 MP3 MP4 Modeled multipath amplitude (db) on vertical OBS channel Rays traced using Bellhop (HLS Research, Inc.) assuming: - depth varying sound speed profile - flat seafloor Transmission loss modeled assuming: - ray divergence - uniform bottom properties Range (km)
11 Model representation of multipath structure Times and amplitudes of multipath arrivals Convolution with autocorrelation of model fin whale call Time (seconds)
12 Range estimation using multipath spacing Modeled multipath arrivals Correlator output of measured call Tracked range = 6 km Cross correlate with Range = 6 m Range = 6 km Range = 15 km Measured call is cross correlated with the multipath model at each range Maximum correlator output at each range is stored Best estimate of range corresponds to maximum correlator output of all possible ranges Time (seconds)
13 Range estimation using multipath spacing Correlator output of measured call Tracked range = 6 km Cross correlate with Cross correlation coefficient Modeled multipath arrivals Range = 6 m Range = 6 km Range = 15 km Range (km) Time (seconds) 25
14 Results: Keck Endeavour Experiment tracked ranges estimated ranges.9.8 Range (km) Cross correlation coefficient Pick number
15 Most common sources of error Range ambiguities related to uncertainties in multipath alignment/identification Errors due to extra arrivals reflected off the base of the sediment layer
16 Range distribution: Keck Endeavour Experiment true range MP range # calls Range (km)
17 Results: Keck Endeavour Experiment 2 tracked ranges estimated ranges.9.8 Range (km) Cross correlation coefficient Pick number
18 Sources of uncertainty : Modeled pick times Direct Range (km) 3 T 1 T T 1 T 2 3 T 1 (seconds) Direct T 2 (seconds)
19 Sources of uncertainty : Modeled pick times Direct Range (km) 3 T 1 T T 1 T 2 3 T 1 (seconds) Direct T 2 (seconds)
20 Sources of uncertainty : Modeled pick times Direct Range (km) 3 T 1 T T 1 (seconds) T 1 T 2 16 km km Direct T 2 (seconds)
21 Measured pick amplitudes 13 Summed multipath energy (db) = 1 standard deviation Range (km)
22 Potential for improvement with flatter, sedimented sites Explorer Plate Endeavour Endeavour 21- Nootka Fault ODP ODP Keck Network Keck Seismometer NEPTUNE Canada Broadband Seismometer Cable Barkley Canyon 29- Elevation, m W 129 W 128 W 127 W 126 W 125 W Pros: More accurate modeling of multipath spacing Amplitude more diagnostic of range Cons: Less energy reflected with each seafloor bounce (multipath suppression)
23 Range distribution: Cascadia Basin 7 Range Distribution: Cascadia Basin 6 5 # Calls Range (km)
24 Cascadia Basin - Zero ranges estimated ranges.9 Range (km) Cross correlation coefficient Pick number.4
25 Cascadia Basin - Zero ranges 1 Smoothed correlator output Best fit model Normalized amplitude Time (seconds)
26 Cascadia Basin - Zero ranges 1 Smoothed correlator output Best fit model Normalized amplitude Two-way travel time Time (seconds)
27 Cascadia Basin - Zero ranges 1 Smoothed correlator output Best fit model Normalized amplitude Time (seconds)
28 Cascadia Basin - Basement reflections SOURCE WATER OBS SEDIMENT BASALT BASEMENT
29 Cascadia Basin - Zero ranges Relative amplitude (db) Sediment thickness ~3m MP 1 MP 1, Path 2 MP 1, Path 3 Paths Distance (km)
30 Cascadia Basin - Zero ranges Time diff (seconds) Amplitude Path 1 (water only) Path Path 3 Paths Sediment thickness (m)
31 Summary The method is working well and is at a stage where we can compare with other methods Remaining issues: Range ambiguities We are exploring ways to constrain solutions in regions of complex bathymetry In some cases more complex modeling schemes might be required to resolve ambiguities Less of an issue in flatter bathymetry Zero ranges (Cascadia Basin) Related to basement reflections Resolved, solution being implemented Funded by:
32
33
34 Cascadia Basin - Zero ranges
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