Approximated Maximum Likelihood algorithm (Sciuridae)

Knowledge graph centered on Approximated Maximum Likelihood algorithm (Sciuridae) with 44 nodes and 140 connections. Top connected: Rocky Mountain Biological Laboratory, Gothic, Marmota, Yellow-bellied Marmot, Callospermophilus lateralis.

Method synopsis

Uses array of wireless acoustic sensors with correlation envelope sum (CES) method to precisely locate sources of marmot alarm calls in field settings. Employs cross-correlation analysis and multilateration algorithms to determine call positions with sub-meter accuracy.

Synthesized from method descriptions across 2 papers using this protocol.

Procedure as described in the canonical source

Steps below were extracted from the paper that introduces this protocol — Is alarm calling risky? Marmots avoid calling from risky places (2010), Ethology. Implementations in other papers (listed below) may differ.

1. Deploy acoustic sensor array
   Established an array of eight VoxNet wireless sensor nodes arranged in a 17-cm tetrahedron configuration with each sensor node consisting of four microphones. The monitored area contained two large burrow complexes with numerous individual burrow openings.
   Quantities: 8 sensor nodes, 4 microphones per node, area approximately 85 × 150 m, deployment density of 10.7 nodes/ha, minimum convex hull enclosing sensors was 7483 m²Duration: Deployed for data collection from August 1-11, 2008Conditions: Summer field conditions at 2900 m elevation near Rocky Mountain Biological Laboratory
   Equipment: VoxNet wireless sensor nodes, microphones, tripods
2. Record acoustic data
   Sensors recorded continuous sound data as 16-bit, 48-kHz PCM files. All recordings were band-pass filtered (2.5-5 kHz) to exclude sounds outside the range of dominant frequencies of marmot alarm calls.
   Quantities: Total of 21.8 hours of recordings from 8 sensor nodes simultaneouslyDuration: August 1-11, 2008, continuous recordingConditions: 24-hour continuous recording in field conditions
   Equipment: VoxNet wireless sensor nodes, data storage systems
3. Localize alarm calls using CES method
   Applied correlation envelope sum (CES) acoustic localization method to determine precise call source locations. Method computes cross-correlations between signal segments from different microphones, uses threshold of 0.75 for peak identification, and applies multilateration algorithm to solve for node positions and orientations. Performed 0.01-m resolution refinement pass over 2 × 2 m lattice centered on maximum value point.

Typical Equipment

• VoxNet wireless sensor nodes
• microphones
• multilateration algorithm
• CES processing software

Output Measurements

• call source coordinates
• acoustic localization precision
• call timing

Papers Using This Protocol (2)

Species Studied With This Protocol

Places Where Used