Collaboration diagram for Tracking:

Classes
struct	cn0_est_state_t
struct	correlation_t
Modules
	Tracking Loops
Functions
void	calc_navigation_measurement (u8 n_channels, channel_measurement_t meas[], navigation_measurement_t nav_meas[], double nav_time, ephemeris_t ephemerides[])
void	calc_navigation_measurement_ (u8 n_channels, channel_measurement_t meas[], navigation_measurement_t nav_meas[], double nav_time, ephemeris_t *ephemerides[])
float	cn0_est (cn0_est_state_t *s, float I)
void	cn0_est_init (cn0_est_state_t *s, float bw, float cn0_0, float cutoff_freq, float loop_freq)

Detailed Description

Functions used in tracking.

Function Documentation

void calc_navigation_measurement	(	u8	n_channels,
		channel_measurement_t	meas[],
		navigation_measurement_t	nav_meas[],
		double	nav_time,
		ephemeris_t	ephemerides[]
	)

Definition at line 453 of file track.c.

void calc_navigation_measurement_	(	u8	n_channels,
		channel_measurement_t *	meas[],
		navigation_measurement_t *	nav_meas[],
		double	nav_time,
		ephemeris_t *	ephemerides[]
	)

Todo:: Handle GPS time properly here, e.g. week rollover

Definition at line 468 of file track.c.

float cn0_est	(	cn0_est_state_t *	s,
		float	I
	)

Estimate the Carrier-to-Noise Density, $ C / N_0 $ of a tracked signal.

Implements a modification of the estimator presented in [1]. In [1] the estimator essentially uses a moving average over the reciprocal of the Signal-to-Noise Ratio (SNR). To reduce memory utilisation a simple IIR low-pass filter is used instead.

The noise and signal powers estimates for the $k$ -th observation, $\hat P_{N, k}$ and $\hat P_{S, k}$ , are calculated as follows:

$\hat P_{N, k} = \left( \left| I_k \right| - \left| I_{k-1} \right| \right)^2$

$\hat P_{S, k} = \frac{1}{2} \left( I_k^2 + I_{k-1}^2 \right)$

Where $I_k$ is the in-phase output of the prompt correlator for the $k$ -th integration period.

The "Noise-to-Signal Ratio" (NSR) is estimated and filtered with a simple low-pass IIR filter:

${NSR}_k = A \frac{\hat P_{N, k}}{\hat P_{S, k}} + (1 - A) {NSR}_{k-1}$

Where the IIR filter coefficient, $A$ can be calculated in terms of a cutoff frequency $f_c$ and the loop update frequency $f = 1/T$ .

$A = \frac{f_c}{f_c + f}$

The filtered NSR value is converted to a $ C / N_0 $ value and returned.

$\left( \frac{C}{N_0} \right)_k = 10 \log_{10} \left( \frac{B_{eqn}}{{NSR}_k} \right)$

References:

"Comparison of Four SNR Estimators for QPSK Modulations", Norman C. Beaulieu, Andrew S. Toms, and David R. Pauluzzi (2000), IEEE Communications Letters, Vol. 4, No. 2
"Are Carrier-to-Noise Algorithms Equivalent in All Situations?" Inside GNSS, Jan / Feb 2010.

Parameters:

s	The estimator state struct to initialise.
I	The prompt in-phase correlation from the tracking correlators.

Returns:: The Carrier-to-Noise Density, , in dBHz.

Definition at line 432 of file track.c.

void cn0_est_init	(	cn0_est_state_t *	s,
		float	bw,
		float	cn0_0,
		float	cutoff_freq,
		float	loop_freq
	)

Initialise the $ C / N_0 $ estimator state.

See cn0_est() for a full description.

Parameters:

s	The estimator state struct to initialise.
bw	The loop noise bandwidth in Hz.
cn0_0	The initial value of in dBHz.
cutoff_freq	The low-pass filter cutoff frequency, , in Hz.
loop_freq	The loop update frequency, , in Hz.

Definition at line 370 of file track.c.

Classes

Modules

Functions

Detailed Description

Function Documentation