The amplitude can be used to determine the maximum range of your measurements. The range is typically limited by either the signal strength reaching the instrument noise floor or by the signal reaching the surface.
As the transmitted signal propagates along the profile, its amplitude decreases continuously due to energy loss from scattering and absorption. Consequently, the strength of the echo signal also decreases, as less energy is available to be reflected. This decay follows the sonar equation and typically resembles the left amplitude profile in Figure 1.
After a gradual decrease in signal strength, the amplitude reaches a constant level known as the noise floor, which is determined by internal electronic noise in the instrument. Beyond this point, the measured signal is dominated by noise, resulting in high variability (standard deviation), and the data should be discarded.
By examining the amplitude profile of a dataset, you can identify where the signal approaches this noise floor. This point defines the effective profiling range and can be used to set an amplitude threshold specific to the instrument and deployment during data processing.
Sidelobe interference
Sidelobe interference is an interference phenomenon that prevents us from measuring currents close to a remote boundary. Sidelobes can be described as energy that "leaks out" from an acoustic beam. These weak signals are sent in multiple different directions than the main lobe. Weak signals that reach a boundary before the main lobe can cause sidelobe interference. This is because boundaries provide a stronger echo than the suspended particles in the water, leading to the received signals from cells near the boundary being dominated and hence contaminated by the sidelobe signals. Roughly speaking, we often say that sidelobe interference can affect up to approximately 10% of the velocity profile between the instrument and the boundary for slanted beams. For further theoretical background please see Sidelobe interference.
Sidelobe interference can be spotted in amplitude profiles, as shown in the right image of Figure 1. When the signal approaches a boundary the signal strength increases until it reaches a maximum value which indicates the boundary. Sidelobes interfere in the area of increase. Sidelobe interference will typically result in a bias toward the velocity of the interfering boundary. For the bottom, this is a bias toward zero (unless there is a moving bottom). The bias will depend on the sea state or surface wind conditions when mearing the sea surface. Sidelobe interference has in many cases been noticed by high velocities in the upper layer. A tip when analyzing data is to check the vertical velocity (Z or Up) extra carefully in this area. It should typically read close to zero. If not, it might be an effect of interference.
Further, the extent to which the sidelobe interference will contaminate the velocity measurements is a function of the boundary conditions, the scattering return strength from the water, and the acoustic properties of the transducers. High scattering strength by the boundary and low scattering return strength from the water makes a greater potential for the sidelobe reflection to dominate the signal. Sidelobe interference may, on the other hand, be unimportant with strong backscatter.
Unfortunately, there is no way in post-processing to separate the bias effect from the sidelobes. Within our processing software, the user can select a percentage of the water column to be rejected. The surface is detected by finding the peak in the acoustic return. A common fraction used is 0.9 (90%).
There are measures that can be taken in advance of a deployment to reduce its impact. One action is to move the instrument closer to the boundary (10% of a short profile is less than 10% of a long profile). Reduction in cell size can also be positive, as this increases the spatial resolution. Also, make sure to keep the instrument as leveled as possible.
How can I increase my profiling range?
The range of your measurements is primarily influenced by fixed parameters like the transducer frequency. You can explore additional factors affecting maximum profiling range in the article What factors affect maximum profiling range? However, there are also configuration measures you can take to influence the range, each with its own set of pros and cons. When configuring your instrument, it's important to consider these factors to optimize its performance for specific applications. It is useful to monitor parameter changes in the "Effect" tab of the applicable Deployment Planning Software, to visualize and understand how your decisions will impact the deployment process.
The table below outlines possible measures to increase range and their potential deployment consequences.
| Measure | Consequence |
| Increase the Power Level | Higher power consumption and therefore shorter deployment |
| Use a larger Cell Size | Lower spatial resolution |
In addition to being governed by the Power Level, the amount of energy the instrument sends out depends on the Cell Size. A small cell size will therefore lead to a relatively lower output power, which again can decrease the actual range of the measurements.
Post-processing software
Storm2 / Ocean Contour
The profiling range and quality of individual datapoints within Storm2 and Ocean Contour is assessed by a combination of Correlation and Amplitude/Signal Strength.
One filter that can be applied is a minimum amplitude threshold. Select the noise floor value specific for your instrument and deployment as the amplitude threshold to filter out data points dominated by noise during processing.
Storm / SeaReport
Our processing tools for the first generation instruments use the so called Signal-to-Noise-ratio (SNR) to determine the valid data range during data processing. A predetermined noise floor, which is unique to each instrument series is compared to the returned signal strength of the profile. The correlation between emitted and received signal typically drops below 50%, as the SNR decreases below 3dB, which is typically recommend as the quality control threshold.
More details about the data processing for each software can be found here:
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