Skip to main content

CI codecov DOI

Underwater Acoustic Channel Toolbox — Python

Generic badge

Python toolbox for replaying signals through measured underwater acoustic channels, generating realistic ocean noise, and unpacking stored impulse responses. To learn more about the channels, check out the documentation.

Please report bugs and suggest enhancements by creating a new issue. We welcome your feedback. See CONTRIBUTING.md for more information.

Installation

pip install uwa-channels

Functions

Function Description
replay Pass a passband signal through a measured underwater acoustic channel.
noisegen Generate realistic ocean noise: pink Gaussian (17 dB/decade), spatially-correlated Gaussian, or impulsive (symmetric α-stable).
unpack Reconstruct the full time-varying impulse response from the compressed representation.

Quick start

Download the channel MAT-files from here and place them in your working directory.

Replay and noise generation

import h5py
from uwa_channels import replay, noisegen

channel = h5py.File("blue_1.mat", "r")
noise = h5py.File("blue_1_noise.mat", "r")

y = replay(input, fs, array_index, channel)
w = noisegen(y.shape, fs, array_index, noise)
r = y + 0.05 * w

See examples/example_replay.py for a complete example that generates a BPSK signal, replays it through the blue_1 channel, adds noise, and plots the received signal, cross-correlation, and spectrum.

Unpack

import h5py
from uwa_channels import unpack

channel = h5py.File("blue_1.mat", "r")
unpacked = unpack(fs_time, array_index, channel)

See examples/example_unpack.py for details.

Channel format

Each channel MAT-file contains:

Variable Description
h_hat Estimated impulse response, shape (K, M, T)
theta_hat or phi_hat Phase or delay-phase trajectory, shape (M, N)
params Group with fs_delay, fs_time, fc
meta Estimation metadata (see estimate repo)
version File format version

Each noise MAT-file contains:

Field Description
Fs Sampling rate at which noise statistics were measured [Hz]
R Signal bandwidth [Hz]
alpha Stability index (2 = Gaussian, < 2 = impulsive)
beta Mixing coefficients, shape (M, M, K)
fc Center frequency [Hz]
rms_power Per-channel RMS power scaling, shape (M, 1)
version Noise struct version

Tests

This repository includes automated testing via GitHub Actions. The tests folder contains three test suites:

Test What it verifies
test_replay Generates random mobile channels ({static, mobile} × {theta_hat, phi_hat}), transmits a signal, and checks that cross-correlation peaks match the true multipath structure.
test_noisegen Verifies output size, spectral shape (17 dB/decade), spatial correlation (theoretical vs. sample), bandpass filtering, rms_power scaling, Gaussianity (α = 2), and heavy-tail behavior (α < 2).
test_unpack Tests all tracking modes (none, theta_hat, phi_hat, f_resamp, and combinations) for correct impulse response reconstruction.

Tests run automatically on every push, ensuring continued correctness of the core functions.

Repository Description
uwa-channels/matlab MATLAB/Octave implementation of the replay toolbox.
uwa-channels/estimate Channel estimation from single-carrier signals, with visualization.

License

The license is available in the LICENSE file within this repository.

© 2025–2026, Underwater Acoustic Channels Group.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

uwa_channels-0.6.4.tar.gz (22.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

uwa_channels-0.6.4-py3-none-any.whl (11.1 kB view details)

Uploaded Python 3

File details

Details for the file uwa_channels-0.6.4.tar.gz.

File metadata

  • Download URL: uwa_channels-0.6.4.tar.gz
  • Upload date:
  • Size: 22.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for uwa_channels-0.6.4.tar.gz
Algorithm Hash digest
SHA256 466f80d8570e1d2401b87ff1deb7c3d9bd8cc14536c18d0990f517f400ef8d12
MD5 faffc8f3912d6366241c80ae96bc570b
BLAKE2b-256 a639e14bf4a68751984ac04dd5a78657c0d21580cf1c7424649aadbb3ee79d54

See more details on using hashes here.

Provenance

The following attestation bundles were made for uwa_channels-0.6.4.tar.gz:

Publisher: ci.yaml on uwa-channels/python

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file uwa_channels-0.6.4-py3-none-any.whl.

File metadata

  • Download URL: uwa_channels-0.6.4-py3-none-any.whl
  • Upload date:
  • Size: 11.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for uwa_channels-0.6.4-py3-none-any.whl
Algorithm Hash digest
SHA256 a93a303feea4dfb3ba8f70d4c38066264d53071635d2c724e298b81d19cc9160
MD5 5127be6a3097108e85d5570a6b48e0bf
BLAKE2b-256 ac964c8719e727a5023870ac81e4750f38a5013cd9ae1ed9c67f1ff3e795e9d1

See more details on using hashes here.

Provenance

The following attestation bundles were made for uwa_channels-0.6.4-py3-none-any.whl:

Publisher: ci.yaml on uwa-channels/python

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.6.7

2 files

0.6.6

2 files

0.6.5

2 files

This release

0.6.4 This release

2 files

0.6.3

2 files

0.6.1

2 files

0.5.7

2 files

0.5.5

2 files

0.5.3

2 files

0.5.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page