MULTIPATH EFFECT ON DPCA MICRONAVIGATION
OF A SYNTHETIC APERTURE SONAR
L. WANG, G. DAVIES, A. BELLETTINI AND M. PINTO
SACLANT Undersea Research Centre, Viale San Bartolomeo 400, 19138 La Spezia, Italy
E-mail: [email protected]
The Displaced Phase Centre Antenna (DPCA) technique makes use of the correlation of
sea bottom back scattering to determine the trajectory of a Synthetic Aperture Sonar
(SAS). Multipath has been identified as the main environmental factor degrading the
accuracy of DPCA in shallow water environments. An experiment has been carried out
with Saclantcen’s 100 kHz multi-aspect SAS demonstrator deployed from R/V Alliance.
The 256 channel receive array was placed, both horizontally and vertically, at various
depths in shallow water channels, in order to quantify the relative levels of the multipath
signals as a function of depth, range, sea state and bottom type. The ping to ping signal
correlation was measured and compared with the results from a sonar performance
model.
1
Introduction
The performance of DPCA micronavigation for SAS applications has been investigated
extensively both in theory and experiment in recent years [1–3]. The technique makes use
of the correlation of the sea bottom back scattering to estimate the displacement of the
sonar between successive pings. The main environmental factor determining the
navigation accuracy achievable for a given sonar system is ultimately the signal to noise
ratio. The signal is the direct sea bottom back scattering, while the noise consists of
background noise of the sea, system noise, surface and volume reverberation and
multipath interference such as surface reflected bottom scattering etc.
When SAS is used in shallow and very shallow waters, the multipath interference
may be a dominant source of noise. Thus the accuracy of the DPCA micronavigation is
degraded, possibly limiting the achievable SAS length. In addition, the multipath will also
degrade the quality of the SAS imagery, leading to ghost targets and loss in image
contrast (e.g. filling in of shadows). Thus multipath could be the most important
environmental factor limiting the range achievable by an SAS system in shallow water.
An experiment has been carried out to investigate the effects of multipath on SAS in
shallow water channels with different water depths and bottom characteristics. A 100 kHz
sonar with a total receiver aperture of 1.92 m was deployed from R/V Alliance in
horizontal and vertical configurations. The data from vertical transmissions provide very
revealing information about the shallow water channel because of the high angular
resolution of the sonar. The signal level and ping to ping correlation were predicted with
a new sonar performance model, ESPRESSO, and compared with the experimental
results.
465
N.G. Pace and F.B. Jensen (eds.), Impact of Littoral Environmental Variability on Acoustic Predictions and
Sonar Performance, 465-472.
© 2002 Kluwer Academic Publishers. Printed in the Netherlands.
466
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Experiment
The experiment was carried out in shallow water near La Spezia (Italy) in two areas, off
Tino island (referred to as area I in the following) and Monesteroli (area II), from the
middle of October to early November, 2001. It was one part of a larger experiment
designed to further the understanding of SAS micronavigation, combining data-driven
techniques such as DPCA and Aided Inertial Navigation Systems. The main piece of
equipment used is the MASAI (Multi Aspect Synthetic Aperture sonar Imaging)
towbody, which consists of a 100 kHz multi-element sonar array and a high grade inertial
navigation system (INS). Figure 1 shows the deployment of the MASAI towbody from
R/V Alliance.
2.1
MASAI System
The MASAI array consists of 256 receiver elements at a 7.5 mm spacing to form an
aperture of 1.92 m. The signal used for MASAI’01 was a 10 ms chirp with 100 kHz
centre frequency and 10 kHz bandwidth. The centre 64 channels were used for
transmission and defocused to give a beam width of 40o. The vertical (resp. horizontal)
beamwidth of the elements was about 40o (resp. 100o). The source level was 206 dB re
1µPa at one meter. The depression angle of the sonar was 22o in the horizontal
configuration.
Figure 1. Deployment of the MASAI system from the Alliance.
MULTIPATH EFFECT ON SAS NAVIGATION
467
The INS used in the MASAI system is a strapdown inertial navigation system with
ring laser gyros. The INS was aided by a 1.2 MHz DVL (Workhorse Navigator by RDI),
a pressure sensor and a GPS. The aiding was peformed with NAVLAB, a software
developed by the Norwegian Defense Research Establishment.
2.2
Environmental Data
The shallow water channels in the location of the trial were flat with a water depth about
26 m in area I and 32 m in area II. Core samples were taken in the areas in order to
determine the bottom characteristics. Two methods were used to obtain the sound speed
and density in the sediments. One was to derive the parameters from grain size of the
sediments and, the other one was to measure directly from the core samples. Table 1
shows the results of grain size analysis for the cores of the top 6 cm in the two areas. It
was observed that the sediment in area I was harder than in area II. Sound speed and
density in the sediments measured directly from the core samples are given in Table 2. It
can be seen that the acoustic impedance of the sediment in area I was much higher than
that in area II.
Wind speed was measured by a meteobuoy during the trial. The measured wind
speeds at the time of sonar transmissions (most of the time corresponding to sea state in
the range 2–3) were used in the sonar model for surface scattering strength and surface
reflection loss. A wave rider was also deployed to measure the wave height.
A CTD was used throughout the trial to obtain the sound speed profile in the water
column in both area I and area II. An isovelocity profile of about 1526 m/s was found for
the whole period.
Table 1. Grain size analysis
Depth (cm)
1.25
3.75
6.25
Tino (area I)
Sand/silt/clay
45.1/46.7/8.1
60.3/33.3/6.0
45.2/49.5/5.2
φ
5.02
4.29
4.95
Monasteroli (area II)
Sand/silt/clay
φ
35.9/40.2/23.9
6.02
29.5/42.8/27.7
6.49
29.6/39.5/26.8
6.17
Table 2. Measured sound speed and density
Depth (cm)
2
3
4
5
6
Tino
Sound speed
(m/s)
1649.66
1643.48
1643.92
1644.47
1639.45
Density
(g/cm3)
1.94
1.92
1.92
1.93
1.91
Monasteroli
Sound speed
Density
(m/s)
(g/cm3)
1549.81
1.74
1550.35
1.72
1552.14
1.72
1557.18
1.79
1556.65
1.79
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L.WANG ET AL.
Sonar model
The modelled data presented in this paper were obtained using a tool being developed at
SACLANTCEN called ESPRESSO. The tool includes a reverberation model based on
the technique of "Geometric beam tracing" [4,5], originally developed to model
propagation loss. The adaptation of this technique to reverberation modelling is described
in [6]. The reverberation model approximates the seabed, sea surface, and water column
as lines of scatterers; the reverberation contribution from each scatterer is allocated to a
time bin to create a reverberation time series. The acoustic models used to obtain
scattering strengths and reflection losses are described in [7] (the bistatic version of the
seabed scattering strength model was used). The absorption coefficient in water was
obtained using the algorithm described in [8].
4
Experimental and modelling results
Although a large amount of data was collected with the sonar in a horizontal
configuration at fixed positions in both areas during the trial, the vertical configuration
was used only in area II. The results presented here are all from the data obtained in area
II since the data from the vertical configuration provided more detailed information about
the channel.
Figure 2. Beamformed sonar data with the array in vertical configuration, showing the arrival
angles of the different paths measured with respect to the vertical.
469
MULTIPATH EFFECT ON SAS NAVIGATION
4.1
Sound Field in the Vertical Plane
In order to study the details of the sound field in the channels, the MASAI sonar was
deployed vertically in area II. The various arrivals can be examined by beamforming the
signals received by the 256 channels, with an angular resolution of 0.45o. One of the
measured sound fields as a function of arrival angle and range is shown in Fig. 2. The
sonar was lowered with ropes from the ship up to a depth of 9.7 m. The transmission
angle was depressed by 6.8 degrees from the horizontal direction, as it was measured by
the INS. This unwanted misalignment was compensated at first order1 by shifting the yaxis origin of Fig. 2.
The lines in the figure indicate where the different arrivals are expected for the given
geometry. The continuous lines are for the direct bottom and direct surface scattering
paths, while the dashed lines give the paths of the specular surface reflection path of the
bottom scattering and its reciprocal path. The signal levels from higher order mutipaths
are too low to be observed.
The measured field reveals that, for a fixed return time, there is a diffuse surface
bounce that spreads much more than what can be explained by the depression angle from
the vertical. This spread is likely to be due to the roughness of the sea surface which
produced non-specular surface reflections from bottom scatterers at closer range than that
corresponding to the specular path. These non-specular returns came from angles of
arrival both larger and smaller than that of the specular path.
Bottom scattering strength
10
0
0
-10
-10
Scattering strength (dB)
Scattering strength (dB)
Surface scattering strength
10
-20
-30
Measured (max)
Measured (mean)
Measured (min)
6 knots
11 knots
-40
-50
-20
-30
Measured (max)
Measured (mean)
Measured (min)
Grain size
Core
-40
-50
-60
-60
0
10
20
30
40
50
60
Grazing angle (deg)
70
80
90
0
10
20
30
40
50
60
Grazing angle (deg)
70
(a)
80
90
(b)
Figure 3. Back scattering strength.
4.2
Measurement of Back Scattering Strength from Sea Surface and Bottom
Direct measurement of the back scattering strength from sea surface was made possible
by the vertical configuration. Figure 3(a) shows the measured surface back scattering
strength as a function of grazing angle using the vertical configuration of the sonar vs the
1
The depression angle causes also a spread in grazing angle (of the same order of magnitude as
the depression angle) for fixed range due to the large horizontal beamwidth.
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L.WANG ET AL.
theoretical model [7]. The measured surface back scattering is plotted in three curves
with minimum, mean and maximum values to indicate the spread of the data. The
measured average wind speed was 11 knots over the period of sonar transmission. Two
curves from the model are given in the figure for wind speed 6 and 11 knots for
comparison. The surface scattering strength was almost constant for grazing angles less
than 30o. The increase of surface scattering strength measured at large grazing angles is
due to the artifact of assuming a sinc beam pattern for the transmitter in the calculation of
the scattering strength. The near constant surface back scattering suggests the main
mechanism of the scattering was due to air bubbles below the surface induced by wind.
The measured bottom back scattering strength is shown in Fig. 3(b) with two
different model predictions. In the first (green line) sound speed and density derived from
logarithmic grain size φ in Table 1 were used (i.e., c = 1506.6 m/s, ρ = 1.183 g/cm3). In
the second (red line) sound speed and density measured from the core sample in table 2
used (i.e., c = 1549.8 m/s, ρ = 1.743 g/cm3). The sediment volume scattering parameter
and loss tangent were adjusted to fit the data. The bottom scattering strength predicted
with the measured sound speed and density from the core is higher than that using
derived results from the grain size analysis. It is likely that the sediment in the core was
compressed during the core sampling process, giving an increase of sound speed and
density in the core samples. It is expected that the true value may be some where in
between the values obtained by the two methods.
Signal level (sonar depth 14.8 m)
Signal level (sonar depth 8.7 m)
160
160
Measured
Grain size
Core
150
140
Signal level (dB)
Signal level (dB)
140
130
120
130
120
110
110
100
100
90
Measured
Grain size
Core
150
0
20
40
60
80
100
120
Range (m)
140
160
180
200
90
0
20
40
60
80
100
120
Range (m)
(a)
140
160
180
200
(b)
Figure 4. Signal level at various sonar depths.
4.3
Signal Level at Various Sonar Depths
Figure 4 shows the received signal from one receiver channel as a function of range at
two different sonar depths, one at about middle depth, the other one at shallower depth.
The signal level predicted by ESPRESSO is in overall agreement with the measured
results, although the model takes only specular reflection into account. Applying the
bottom parameters obtained from grain size analysis results in a better prediction of the
signal level, while using the direct measured parameters from the core sample results in a
prediction higher than the measured data at longer ranges.
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MULTIPATH EFFECT ON SAS NAVIGATION
4.4
Ping to Ping Correlation at Various Sonar Depths
DPCA makes use of the correlation of direct sea bottom back scattering between
successive pings to estimate the displacement of the sonar. The received signal by the
MASAI sonar at ping k can be expressed as
Xk (t)=sk(t)+nk(t)
(1)
where sk(t) is the direct bottom scattering and nk(t) is the interference including
background noise and multipath signals.
The predicted values of the correlation coefficient µ, derived from the modelled
signal to noise ratio, are plotted in Fig. 5 together with the corresponding experimental
results. It is seen that there are large variations between the two sets of modelled data and
that the agreement between the modelled and measured data is not very good.
For both models, the correlation peaks at close range, before the onset of
multipathing and then decreases as the specular multipath enters into the sonar through
the sidelobes of the vertical beam pattern. The correlation then increases again, as the
specular multipath falls into the null of the vertical beampattern, to again decrease with
range as this nulling effect diminishes. In addition both sets of modelled data predict the
onset of higher order multipath at long ranges, which is more important for the model
with higher impedance and sound speed in the sediment (in particular giving a higher
critical angle).
Ping to ping correlation (sonar depth 14.8 m)
Ping to ping correlation (sonar depth: 8.7 m)
1
1
Measured
Grain size
Core
0.8
0.8
0.7
0.7
0.6
0.5
0.4
0.6
0.5
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0
0
20
40
60
80
100
120
Range (m)
140
160
(a)
180
Measured
Grain size
Core
0.9
Correlation coef
Correlation coef
0.9
200
0
0
20
40
60
80
100
120
Range (m)
140
160
180
200
(b)
Figure 5. Signal correlation at different sonar depths.
In the experimental data, the correlation peaks at close range. The low values
obtained at very short range are probably due to baseline decorrelation, resulting from
residual motion of the sonar between pings and the high grazing angles of operation. The
peak correlation coefficient increases with the sonar depth, as a result of the reduced sea
surface interactions. The correlation then seems to decrease monotonically with range.
The increase predicted by the models, due to the nulling of the specular multipath by the
vertical beampattern, is not observed. This is indicative of the diffuse nature of the
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L.WANG ET AL.
multipathing. The decrease in the correlation with range is faster for the deeper sonar
position [Fig. 5(a)] than for the shallower one [Fig. 5(b)], predominantly as a result of the
reduction in the grazing angle for given slant range.
5
Summary
The effects of multipath on DPCA micronavigation were studied experimentally.
Comparisons between the experimental results and sonar model predictions seem to
indicate that the diffuse surface reflection significantly affected the signal correlation.
More analysis is required to confirm this assumption. It may be necessary to extend sonar
models beyond the specular reflection scenario to take this effect into account.
Acknowledgements
We thank all the people involved in the MASAI’01 experiment. We also thank Eric
Pouliquen for his help.
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