Detection¶
Detectors¶
- class sdr.ReplicaCorrelator
Implements an clairvoyant replica-correlator detector.
- class sdr.EnergyDetector
Implements an energy detector.
Coherent integration¶
- sdr.coherent_gain(n_c: ArrayLike) NDArray[float64]
Computes the SNR improvement by coherently integrating \(N_C\) samples.
- sdr.coherent_gain_loss(integration_time, ...) NDArray[float64]
Computes the coherent gain loss (CGL) as a function of the given integration time and frequency offset.
- sdr.max_integration_time(cgl: ArrayLike, ...) NDArray[float32]
Computes the maximum integration time that produces at most the provided coherent gain loss (CGL).
- sdr.max_frequency_offset(cgl: ArrayLike, ...) NDArray[float32]
Computes the maximum frequency offset that produces at most the provided coherent gain loss (CGL).
Non-coherent integration¶
- sdr.non_coherent_gain(n_nc: ArrayLike, snr, ...) NDArray[float64]
Computes the SNR improvement by non-coherently integrating \(N_{NC}\) samples.
Theoretical limits¶
- sdr.albersheim(p_d: ArrayLike, p_fa, ...) NDArray[float64]
Estimates the minimum required single-sample SNR.
Last update:
Mar 02, 2024