CORRELATION BETWEEN SONAR ECHOES AND SEA BOTTOM TOPOGRAPHY

Transcription

1 CORRELATION BETWEEN SONAR ECHOES AND SEA BOTTOM TOPOGRAPHY JON WEGGE Norwegian Defence Research Establishment (FFI), PO Box 115, NO-3191 Horten, Norway False alarms resulting from sonar signals reflected off the sea floor terrain are of great concern in littoral waters. Series of these alarms often resembles a footprint of the topography. This gives rise to the idea of predicting the positions of such alarms using detailed terrain maps. In addition to the sound speed profile, the success of such a solution depends on the local sea floor composition in addition to the topography and the relative position of the sonar platform. This paper compares high-resolution bathymetric data with the positions of sonar alarms generated from a sequence of pings using a 7 khz hull mounted sonar. The experiment is based on data recorded in a Norwegian fjord. The results show good correlation between sonar echo clusters and topographic features. 1 Introduction At an early processing stage, the active sonar signal is passed through a detector to generate detections or alarms, or echoes which is the term used in this paper. As the number of sonar echoes generated during anti-submarine warfare (ASW) operations far outnumber the targets present, most of the echoes are false alarms. The topic of false alarms processing is becoming increasingly important with the increased detection capability of modern long range sonars and the focus on ASW capabilities in littoral waters. More alarms or sonar echoes are generated due to increased noise and reverberation, in particular bottom reverberation in fjords and coastal waters. The reason is the nature of the bottom topography and man-made objects on the sea floor. Although man-made objects like wrecks and pipelines usually generate submarine like echoes, the topographic features will outnumber the man-made objects in most areas. The intensity of bottom reverberation not only depends on the bottom characteristics, but also on the sea floor depth and the sound speed profile. Some of these influences may be compensated for by adjusting the operation of the sonar, e.g. by tilting the sonar beams. Naval vessels are also maneuvered to reduce the level of reverberation in search areas. This limits the number of possible paths followed by the sonar platform, and enemy submarines may exploit this in order to minimize the probability of detection. A somewhat higher reverberation level could be tolerated if one could discriminate target echoes against echoes from bottom features. Conditions for such a method is a detailed topographic map including sub-bottom information. 319 N.G. Pace and F.B. Jensen (eds.), Impact of Littoral Environmental Variability on Acoustic Predictions and Sonar Performance, Kluwer Academic Publishers. Printed in the Netherlands.

2 320 J. WEGGE This paper will show correlation between sonar echoes and topography. It will also demonstrate the prediction of sonar echo clusters by applying detailed topographic and oceanographic information to simulations using the LYBIN hydroacoustic model. 2 The experiment The objective of this work was to conduct a visual investigation of how the sonar echo positions recorded on the Oslo-class frigates' hull mounted sonar (HMS) Spherion, correlate with high resolution sea-floor topography data of. This analysis not only addresses the effect the topography has on echoes, but also the potential effect it has on the generation of tracks. Such tracks are based on series of echoes from topography and may be challenging for an operator to discriminate from real target tracks. This study operates on a set of topographical data originating from raw data recorded by FFI using multi-beam sonar. Topographic data are compiled from several runs and have a depth resolution of about 1 m, but is also prone to errors in terms of peaks up to 200 m above the sea floor near great rifts and edges. This is clearly shown in the contour graphs in this paper. The range resolution is better than 10 m. No additional information about the bottom or objects on the bottom is taken into account. Comparison between bottom reverberation and topography has earlier been conducted elsewhere by Preston et al. at SACLANTCEN [1]. Figure 1. Frigate path is shown at the bottom where beam borders are drawn at pings 300 (right), 550 and 800 (left) as dashed lines in blue, green and red colours respectively. Axis values are in terms of meters from start of sonar run.

3 CORRELATION BETWEEN SONAR ECHOES AND TOPOGRAPHY 321 The Spherion sonar was delivered by Thales Underwater Systems and has 36 fixed receiver beams, 7 khz center frequency, 500 Hz bandwidth, approximately 13º horizontal and vertical beamwidth and was doing FM-processing (match filtering), normalization, size filtering, clustering and thresholding to generate the echoes recorded. The data were recorded during a sea trial in April with sea state 1 and a surface duct reaching down to 50 m. Figure 1 shows the run with the sonar platform path at the bottom and the area under observation at the top. The lines extending from the sonar platform, show the direction and distance from the sonar at the different pings. 3 Echoes plotted on top of topographic data The echo parameters recorded during the sea trial consist of the ping number, type of processing, their displacements from sonar platform in terms of meters in northern and eastern direction in addition to their respective signal-to-noise ratio as estimated by the Spherion sonar processing on board the frigate. As the position of the frigate for each ping was recorded, the absolute position of a reflector, giving rise to an echo, may be estimated. The deviation of the estimated echo position may be up to 100 m in isolated cases. However, the standard deviation is belied to be better than 25 m in both directions. In the figures displaying the topography in this paper, the contours of the topography are drawn as coloured lines where purple and dark blue contours are depths of about 700 m and deep red contours are 0m topography depth. The contour interval is 20 m. The high-resolution (1 m in depth and 10 m in range) data in this analysis cover an open fjord region measuring 2 by 2.5 km. Outside this area, a range resolution at 50 m is used. The borders separating the beams of the hull-mounted sonar are drawn for ping 300, 550 and 800 as straight lines in blue, green and red respectively. The same colours are used for plotting the echoes of the corresponding pings and intermediate pings (blue, green, yellow, orange, red). 3.1 Proximity Filtering of Echoes Echoes estimated from a single sonar ping produce a display filled with almost randomly scattered echoes when plotted according to their relative position to the sonar platform. Many echoes seem to have random positions, they do not normally appear at the same positions in the following pings. This is caused by the combined influence of noise and all classes of reverberation at each ping. A filtering method was introduced to exclude the echoes not having any close neighbour echoes within the most recent pings. The processing considers each ping and searches for one or more echoes over the ten previous pings within a box measuring 50 by 50 m centered on the echo. If no echoes are found, the echo under analysis will not be drawn. This proximity filtering reduces the number of echoes so that only phenomena repeatedly generating echoes are plotted. Hence echoes caused by more random signal spikes are filtered out. The method of course has a weakness in leaving out any isolated weak signals, which might be a target. This is not considered significant, as the objective of this analysis is to investigate the correlation between topography and sonar echoes from a HMS sonar.

4 322 J. WEGGE Figure 2. Echoes from ping proximity filtered using 50 m and 10 pings and plotted over a 10-m resolution contour map. The echoes are coloured according to their history. Axis values are in terms of meters from start of sonar run. Among other observations, it is worth mentioning how animations of sequential ping-images were effective for observing trends/dynamics in the scenario as opposed to stills. Including making clear observation of (surface) vessels, it was shown how topography gives rise to false moving targets as the position of sonar platform is changing. 3.2 Detailed Study of Topographic Phenomena From the area covered by Fig. 2, an area measuring 1000 by 800 m was chosen as an open fjord area in this analysis (Fig. 3). The depth in this region ranges from 120 m (orange) to 500 m (dark blue). The main characteristic of the topography is a plateau in the north which taper off in the south-eastern direction, first more gently, then more sudden. In the southern direction the plateau falls off roughly 200 m in a 30 m range. The whole area is tilted towards the frigate in the run used in this analysis. The distance from the sonar platform to this area ranges from 4 km to about 3 km. All topography charts shown in this report contain data errors that appear as spikes in the topography charts. Both clear green and red echoes seem to cluster near or on top of sharp edges in the topography. Where the slope is more moderate, the echo density is clearly lower. This can

5 CORRELATION BETWEEN SONAR ECHOES AND TOPOGRAPHY 323 only be shown using charts having high-resolution topography data as used in this paper. This also enables observation of small topographic variations that cause the clustering of echoes. It is also worth noting the low echo density in the flat or close to flat areas where proximity filtering was not applied, which means that mainly reverberation and not noise is the main cause for these echoes. Analysis has shown that most echoes have a low signal-to-noise ratio (SNR). This is partly caused by their relative position with respect to the sonar platform. Another cause is the channel condition we have which traps a lot of the acoustic energy in a surface channel reaching not deeper than 50 m. As the most shallow area within the window is 200 m, very few strong echoes can be expected. Observations not documented here also revealed that all echoes of medium to high signal to noise ratio appear at the sloped area. Figure 3. Proximity filtered echoes colour coded according to the time of their ping. The striped lines correspond to the beam borders at ping 300 (blue), 550 and 800 (red). The colour of the beam borders corresponds to the colour of the echoes at time of the ping. Axis values in terms of meters from start of sonar run. As most echoes here have a low SNR, no alarms would normally be generated when filtering echoes based on their SNR. However, if full sensitivity were desirable, all echoes would be subject of analysis. Then the likelihood of several echoes being present within a small area would have been greater, and likewise the initiation of tracks. This would then have increased the probability of false alarm. Echoes generated by topographic features are the most probable cause for these alarms. By understanding what characteristics of the topography give rise to echoes, one may therefore be able to predict areas where there is a high probability of alarms. This has been observed by animating the pings: the echoes from e.g. a sea-floor slope appear to be moving as the sonar platform moves along. The reason being the point of specular reflection moves as the ship moves past the slope. This might lead to generation of track with realistic speed and heading. When investigating Fig. 3 in detail and taking the uncertainty of echo position into account, it may be suspected that the red echo cluster around x,y-position (-7350, 1650) is caused by the turbulence in the topography in the same area.

6 324 J. WEGGE However, hydroacoustic modeling described in the next chapter revealed a minimum for the transmission loss and a peak in reverberation at this depth and range. This causes the energy weighting of the sonar processing to generate echoes. 4 Analysis of hydroacoustic model simulations The range dependent LYBIN hydroacoustic model was used to simulate sonar performance. Figure 4 shows the simulations for ping no The bottom profile, which was extending 5 km from the sonar position at 25º bearing, was compiled from both 10 m and 50 m resolution topography data. The figure also contains a plot of the topography and sonar echoes at the left (echoes of ping 800 are red). Estimated noise and reverberation curves are drawn at the top right-hand side. The transmission loss and sound profile are shown on the lower right-hand side. A wind speed of 1 m/s and bottom type 2 (rock-gravel) were used as environmental parameters. Even if much of the energy is trapped in the surface duct (see the transmission loss diagram), enough energy reaches the bottom and makes high bottom reverberation possible. Apart from exceeding the bottom reverberation at 1700 m, the surface reverberation is db lower than the bottom reverberation from 2 km and outward. Volume reverberation seems to be high over the whole range and dominates up to 2.5 km. Further out in range, the acoustic energy reflected within the surface duct is exceeded by the bottom reflections. Hence, the bottom reverberation dominates. As the bottom rises sharply, the transmission loss reaches a minimum along the bottom at 2.7 km before it increases again. At 2.7 km the bottom reverberation also peaks which coincide with the clustering of echoes. The peak of the bottom reverberation at 3.7 km is identified as the surface duct sound energy reflecting from the slightly shallower area at this range and bearing. This correlates with the echoes shown in the topography charts. The bottom profile was smoothed in this investigation to avoid any potential influence caused by the artificial peaks in the topography charts. Despite of the interpolation of the bottom profile within LYBIN, error correction of the topography charts are recommended before a more thorough study of topography correlation of sonar echoes. It is also recommended to increase the range resolution of the model to investigate the details of reverberation data further. 5 Conclusion Sonar echo data from the Spherion HMS have been analyzed and compared with topographic data. Echoes are observed to cluster where the bottom is sloping steeply towards the sonar and the transmission loss is low. It was not possible to correlate all echoes with topographic features. One reason may be that a contour distance of 20 m was used despite the 1-m resolution of the topography data. This study was based on only a single set of sonar data from a single hull mounted sonar. The data were recorded in a Norwegian fjord in the month of April. The study has neither considered the accuracy of platform positions or the position accuracy of the sonar echoes recorded. However, any deviation from true position is believed to be insignificant for this study, as there seems to be a close correlation between topography and sonar echo positions.

7 CORRELATION BETWEEN SONAR ECHOES AND TOPOGRAPHY 325 B V NL S Figure 4. Topography and proximity filtered echoes from Fig. 2 are shown at the left. Curves for noise and volume, surface and bottom reverberation at the top right-hand side (in green, red, blue and orange colours respectively). Below this is a plot of sound speed profile and the transmission loss. The orange coloured vertical lines in the reverberation and transmission loss diagrams signify the start and stop of the red line with orange squares in the topography diagram. The topography data presented here have a range resolution of 10 m. Even with topography data not as detailed as this, the sub-sea landscape will provide clues to the majority of echoes not caused by the submarine. Large sea-floor landscape types exist which explain most of these false alarms or echo clusters. Examples of such landscape types are local sea-floor peaks, hillsides with favorable reflecting angel or simply sea floor sufficiently shallow to coincide with the surface channel. However, this study has shown the increased capability of explaining potential false alarm and false targets using high-resolution topography information. This investigation looked into the possibility of correlation sonar echoes with topographic features using only a few numbers of presentation methods. For a more complete manual classification of sonar echoes, a flexible display enabling correlation of sonar echoes with high-resolution topography data and modeled hydro-acoustic data, must be made available. Such a system should be complemented with target tracking and other algorithms for estimating the probability parameters of echoes. It might also prove

8 326 J. WEGGE beneficial to base the processing on a more basic data level than the Spherion sonar echo level used for this study. Acknowledgements The author would like to thank Elling Tveit for his guidance and co-operation during the preparation of this paper. References 1. Preston, J.R., Ellis, D.D., Akal, T. and Desharnais, F., Analysis of low frequency acoustic reverberation in the western Black Sea. SACLANTCEN Report SR-286 (1998).