Preparing instrument scanning data for school detection

The instrument scanning school detection algorithm partitions data into frames. This applies only to data collected by instrument scanning.

This page outlines recommended steps to prepare your data for school detection from such data. If you encounter any problems detecting schools on instrument scanned data we strongly recommend you follow these steps.

1. Identify your variables
   1. Display the Dataflow window
   2. Identify the position variable you intend to use (it is probably connected to the platform)
   3. Identify the acoustic variable you intend to use (it must be an H-mode or V-mode variable recorded by instrument scanning)

   If you don't have these two variables you cannot continue with school detection.

2. (highly recommended applied to a raw variable, prior to other operators, analysis or processing) correct data for motion (pitch and roll):
   1. Create a virtual variable from your chosen acoustic variable using the Motion correction (Dunford method) operator.
   2. Select a desired variable from the Operand 1 list of the Variable Properties dialog box.
   3. Select a roll variable from the Operand 2 list.
   4. Select a pitch variable from the Operand 3 list.
   5. On the Calibration page, in the Inherit calibration settings from: section, select the variable you nominated as Operand 1.

   The resultant virtual variable can then be processed and analyzed as normal.

   See Using the motion correction operator for more information.

   Other features that correct for vessel motion include heave compensation (applied to a platform), Motion range bitmap, and Multibeam roll at transducer.
3. (optional) smooth the position data:
   1. Create a virtual variable from your chosen position variable using the Kalman GPS filter operator.
   2. Select the desired position variable on the Operands page of the Variable Properties dialog box.
   3. Set the degree of smoothing on the Smoothing page of the Variable Properties dialog box.
   4. Select the smoothed position variable on the Position page of the Platform Properties dialog box.

   The resultant virtual position variable contains data that has been smoothed with a Kalman filter.

   The Notes page of the Variable properties dialog box for the virtual variable displays the Operator statistics for the smoothing.

4. (highly recommended) add heading data to the platform:
   1. Select the heading data (not heading from the cruise track) on the Attitude page of the Platform Properties dialog box.

You are now ready to detect 3D schools. See Creating 3D regions for more information.

Notes:

• Consider removing noise from the multibeam variable with noise removal operators.
• Consider excluding unwanted data with detected or virtual surfaces. See also About surfaces.

See also

Creating 3D regions
About school detection algorithms
3D school detection algorithms for Instrument scanning