Use uppercase subscripts

src/sdr/_estimation/_time.py

@@ -25,14 +25,14 @@ def tdoa_crlb(
  Calculates the Cramér-Rao lower bound (CRLB) on the time difference of arrival (TDOA) estimation.
 
  Arguments:
- snr1: The signal-to-noise ratio (SNR) of the first signal $\gamma_1 = S_1 / (N_0 B_n)$ in dB.
- snr2: The signal-to-noise ratio (SNR) of the second signal $\gamma_2 = S_2 / (N_0 B_n)$ in dB.
+ snr1: The signal-to-noise ratio (SNR) of the first signal $\gamma_1 = S_1 / (N_0 B_N)$ in dB.
+ snr2: The signal-to-noise ratio (SNR) of the second signal $\gamma_2 = S_2 / (N_0 B_N)$ in dB.
  time: The integration time $T$ in seconds.
- bandwidth: The signal bandwidth $B_s$ in Hz.
- rms_bandwidth: 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: The noise bandwidth $B_n$ in Hz. If `None`, the noise bandwidth is assumed to be the
- signal bandwidth $B_s$. The noise bandwidth must be the same for both signals.
+ bandwidth: The signal bandwidth $B_S$ in Hz.
+ rms_bandwidth: 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: The noise bandwidth $B_N$ in Hz. If `None`, the noise bandwidth is assumed to be the
+ signal bandwidth $B_S$. The noise bandwidth must be the same for both signals.
 
  Returns:
  The Cramér-Rao lower bound (CRLB) on the time difference of arrival (TDOA) estimation standard deviation
@@ -42,10 +42,10 @@ def tdoa_crlb(
  The Cramér-Rao lower bound (CRLB) on the time difference of arrival (TDOA) estimation standard deviation
  $\sigma_{\text{TDOA}}$ is given by
 
- $$\sigma_{\text{TDOA}} = \frac{1}{2 \pi B_{s,\text{rms}}} \frac{1}{\sqrt{B_n T \gamma}} .$$
+ $$\sigma_{\text{TDOA}} = \frac{1}{2 \pi B_{S,\text{rms}}} \frac{1}{\sqrt{B_N T \gamma}} .$$
 
  The effective 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
+ time-bandwidth product $B_N T$. The product $B_N T \gamma$ is the output SNR of the matched filter
  or correlator.
 
  The time measurement accuracy is inversely proportional to the bandwidth of the signal and the square root of