Noise, background object and attenuated signal removal in Echoview

This page outlines methods with which you can address the issues of noise, background object or attenuated signal in your acoustic data using Echoview.

Data thresholding

Where your targets have good signal to noise ratio (the background noise is low level when compared to the signal you are interested in) then it may be sufficient to ignore all data below a certain threshold.

Single beam data

Four thresholds can be applied to single beam Sv data in Echoview (handling is similar for other data types such as TS data):


Multibeam data

Three thresholds can be applied to multibeam Sv data in Echoview:

Background noise subtraction

Where there is a target with a low signal to noise ratio it may not be appropriate to correct for background noise by thresholding, an alternative (and physically correct approach) is to correct for noise by subtraction. The papers cited in the References page of this help file may provide useful reading on this topic.

Note: If correcting for noise by subtraction then NO thresholds should first be applied to the data.

Using analysis variables

In this case mean Sv and mean noise Sv (or equivalent area variables) are calculated over integration cells and the mean noise is subtracted from the total of noise plus target outside of Echoview as follows:

  1. select the desired background noise analysis variables (on the Export page of the EV file properties dialog)
  2. specify a noise Sv at 1 m (on the Analysis page of the Variable Properties dialog box)
  3. specify the absorption coefficient (on the Calibration page of the Variable Properties dialog box)
  4. specify the TVG range correction setting (on the Calibration page of the Variable Properties dialog box)
  5. Export integration results (see Exporting integrations)
  6. The noise analysis variables are exported along with integration results. You must perform the subtraction external of Echoview with whatever tool you are most comfortable with for downstream analysis.

Note: From Echoview 4.20 onwards, if a TVG range correction is applied on the Calibration 2 page (from Echoview 5.0 aka Calibration page) of the Variable Properties dialog box, then this correction is also used in the background noise analysis variable calculations. Previously, Echoview did not account for TVG range correction in such calculations. As a consequence there may be small but significant errors in the TVT data. The errors are of the order of 0.5dB (at 2m) to 0.05 dB (at 17m).

Using operators

TVG-noise stripes on an Sv echogram are a type of background noise.

Estimate background nosie and subtract

Figure 1: Sv echogram with TVG-noise stripes, Data generator operator configured for a Constant + TVG curve noise estimate, Linear minus operator for Sv - noise estimate.

Background noise removal

The Background noise removal operator removes background noise for single beam and multibeam Sv, TS and Power dB variables. The Background Noise Removal algorithm assumes that some portion of the sampled acoustic signal is dominated by background noise. It estimates the background noise value for each ping and subtracts it from the ping's samples. The algorithm analyzes the echogram by averaging the sample values within averaging cells around each ping. The averaging cells have a fixed horizontal extent in pings and a fixed vertical extent in samples. The noise estimate for a ping is the minimum of its cell averages.

You can specify six settings on the Background Noise Removal page of the Variable Properties dialog box. Four settings specify the averaging cell used to determine the noise estimate. Two Threshold settings set the Maximum Noise and Minimum SNR.

The algorithm uses concepts discussed in "A post-processing technique to estimate the signal-to-noise ratio and remove echosounder background noise." by A. De Robertis and I. Higginbottom (2007). The algorithm page discusses background noise removal strategies that may be helpful with low SNR data.

Multibeam background removal

The Multibeam background removal operator calculates a statistic from a window of pings around the current ping. This statistic is intended to capture the static background elements present in the data. It then subtracts that statistic from the current ping, leaving the data without the background.

Kovesi image denoising

Kovesi image denoising algorithms have been adapted for use in Echoview with multibeam imaging sonar data from a MATLAB script copyrighted by Peter Kovesi. The algorithm doesn't distort data and it preserves image detail. Imaging sonar data may benefit by using the Kovesi image denoising operator prior to using the Multibeam background removal operator.

Note: The Kovesi image denoising requires a lot of processing.

Impulse noise removal

Impulse noise may be caused by interference from other sonars which manifest as short ‘flecks’ on an echogram. The Impulse noise removal operator identifies and adjusts sample values that are significantly higher than those of surrounding samples at the same depth.

Transient noise removal

Transient noise may be sound generated by wave-hull collisions which manifest as long ‘spikes’ on an echogram. The Transient noise removal operator identifies and adjusts sample values that are significantly higher than those of surrounding samples.

Attenuated signal removal

An attenuated signal may appear as missing pings or pings with significantly weaker echoes than surrounding pings. This Attenuated signal removal operator identifies and adjusts pings which show an attenuated signal strength when compared to the surrounding pings.

See also

About algorithms
Background noise calculation
Background noise subtraction references
Time-varied threshold algorithm
About time varied gain