signals

This module is used to define the radar network configuration.

Module summary

Functions

hard_target_rcs(wavelength, diameter)

Determine the radar cross section for a hard target.

hard_target_snr(gain_tx, gain_rx, …[, …])

Determine the signal-to-noise ratio (energy-to-noise) ratio for a hard target.

Contents

Functions

sorts.signals.hard_target_rcs(wavelength, diameter)[source]

Determine the radar cross section for a hard target. Assume a smooth transition between Rayleigh and optical scattering. Ignore Mie regime and use either optical or Rayleigh scatter.

Parameters

  • wavelength (float) – radar wavelength (meters)

  • diameter (float/numpy.ndarray) – diameter in meters of the objects.

sorts.signals.hard_target_snr(gain_tx, gain_rx, wavelength, power_tx, range_tx_m, range_rx_m, diameter=0.01, bandwidth=10, rx_noise_temp=150.0)[source]

Determine the signal-to-noise ratio (energy-to-noise) ratio for a hard target. Assume a smooth transition between Rayleigh and optical scattering. Ignore Mie regime and use either optical or Rayleigh scatter.

Parameters

  • gain_tx (float/numpy.ndarray) – transmit antenna gain, linear

  • gain_rx (float/numpy.ndarray) – receiver antenna gain, linear

  • wavelength (float) – radar wavelength (meters)

  • power_tx (float) – transmit power (W)

  • range_tx_m (float/numpy.ndarray) – range from transmitter to target (meters)

  • range_rx_m (float/numpy.ndarray) – range from target to receiver (meters)

  • diameter (float) – object diameter (meters)

  • bandwidth (float) – effective receiver noise bandwidth for incoherent integration (tx_len*n_ipp/sample_rate)

  • rx_noise_temp (float) – receiver noise temperature (K)

Returns

signal-to-noise ratio

Return type

float/numpy.ndarray

Reference: Markkanen et.al., 1999