-
sdr.toa_crlb(snr: ArrayLike, time: ArrayLike, bandwidth: ArrayLike, rms_bandwidth: ArrayLike | None =
None
, noise_bandwidth: ArrayLike | None =None
) NDArray[float64] Calculates the Cramér-Rao lower bound (CRLB) on time of arrival (TOA) estimation.
- Parameters:¶
- snr: ArrayLike¶
The signal-to-noise ratio (SNR) of the signal \(\gamma = S / (N_0 B_n)\) in dB.
- time: ArrayLike¶
The integration time \(T\) in seconds.
- bandwidth: ArrayLike¶
The signal bandwidth \(B_s\) in Hz.
- rms_bandwidth: ArrayLike | None =
None
¶ The root-mean-square (RMS) bandwidth \(B_{s,\text{rms}}\) in Hz. If
None
, the RMS bandwidth is calculated assuming a rectangular spectrum, \(B_{s,\text{rms}} = B_s/\sqrt{12}\).- noise_bandwidth: ArrayLike | None =
None
¶ The noise bandwidth \(B_n\) in Hz. If
None
, the noise bandwidth is assumed to be the signal bandwidth \(B_s\).
- Returns:¶
The Cramér-Rao lower bound (CRLB) on the time of arrival (TOA) estimation error standard deviation \(\sigma_{\text{toa}}\) in seconds.
See also
Notes
The Cramér-Rao lower bound (CRLB) on the time of arrival (TOA) estimation error standard deviation \(\sigma_{\text{toa}}\) is given by
\[\sigma_{\text{toa}} = \frac{1}{\pi \sqrt{8} B_{s,\text{rms}}} \frac{1}{\sqrt{B_n T \gamma}}\]\[ B_{s,\text{rms}} = \sqrt{\frac {\int_{-\infty}^{\infty} (f - \mu_f)^2 \cdot S(f - \mu_f) \, df} {\int_{-\infty}^{\infty} S(f - \mu_f) \, df} } \]where \(\gamma\) is the signal-to-noise ratio (SNR), \(S(f)\) is the power spectral density (PSD) of the signal, and \(\mu_f\) is the centroid of the PSD.
Note
The constant terms from Stein’s original equations were rearranged. The factor of 2 was removed from \(\gamma\) and the factor of \(2\pi\) was removed from \(B_{s,\text{rms}}\) and incorporated into the CRLB equation.
The signal-to-noise ratio (SNR) \(\gamma\) is improved by the coherent integration gain, which is the time-bandwidth product \(B_n T\). The product \(B_n T \gamma\) is the output SNR of the matched filter or correlator, which is equivalent to \(E / N_0\).
\[B_n T \gamma = B_n T \frac{S}{N_0 B_n} = \frac{S T}{N_0} = \frac{E}{N_0}\]Warning
According to Stein, the CRLB equation only holds for output SNRs greater than 10 dB. This ensures there is sufficient SNR to correctly identify the time/frequency peak without high \(P_{fa}\). Given the rearrangement of scaling factors, CRLB values with output SNRs less than 7 dB are set to NaN.
The time measurement precision is inversely proportional to the bandwidth of the signal and the square root of the output SNR.
Examples
In [1]: snr = 10 In [2]: time = np.logspace(-6, 0, 101) In [3]: plt.figure(); \ ...: plt.loglog(time, sdr.toa_crlb(snr, time, 1e5), label="100 kHz"); \ ...: plt.loglog(time, sdr.toa_crlb(snr, time, 1e6), label="1 MHz"); \ ...: plt.loglog(time, sdr.toa_crlb(snr, time, 1e7), label="10 MHz"); \ ...: plt.loglog(time, sdr.toa_crlb(snr, time, 1e8), label="100 MHz"); \ ...: plt.legend(title="Bandwidth"); \ ...: plt.xlim(1e-6, 1e0); \ ...: plt.ylim(1e-12, 1e-6); \ ...: plt.xlabel("Integration time (s), $T$"); \ ...: plt.ylabel(r"CRLB on TOA (s), $\sigma_{\text{toa}}$"); \ ...: plt.title(f"Cramér-Rao lower bound (CRLB) on TOA estimation error\nstandard deviation with {snr}-dB SNR"); ...: