GPS World, February 2014

SIGNAL PROCESSING Ubiquitous Positioning joint 3D signal image signal energy versus code phase and Doppler shift Signal parameters code phase Doppler shift carrier phase are then estimated directly from this image and without employing tracking loops Open loop tracking is directly applied to accommodate limitations of military and civilian data links To support the functionality of the receiver network at the signal processing level that is to enable multi platform signal tracking and multi platform phased arrays while satisfying bandwidth limitations of existing data link standards individual receivers exchange pre correlated signal functions rather than exchanging raw signal samples Before sending its data to others each receiver processes the incoming satellite signal with a preprocessing engine This engine accumulates a complex amplitude of the GNSS signal as a function of code phase and Doppler frequency shift Receivers then broadcast portions of their pre correlated signal images that are represented as a complex signal amplitude over the code Doppler correlation space for 1 ms or 20 ms signal accumulation For broadcasting portions of signal images are selected around expected energy peaks whose locations are derived from some initial navigation and clock knowledge This approach is scalable for the increased number of networked receivers and or increased sampling rate of the ranging code such as P Y code vs CA code The link bandwidth is accommodated by tightening the uncertainty in the location of the energy peak As a result the choice of the data link becomes a trade off between the number of collaborative receivers and MUSTER cold start capabilities that is maximum initial uncertainties in the navigation and clock solution Multi Node Signal Accumulation An earlier paper that we presented at the ION International Technical Meeting January 2013 describes the approach of multi platform signal accumulation for those cases where relative multi node navigation and clock states are partially known This section reviews that approach and then extends it to cases of completely unknown relative navigation and clock states The following assumptions were previously used Relative position between networked receivers is known only within 100 meters Relative receivers velocity is known within 2 meters second Relative clock states are calibrated with the accuracy of 100 nanoseconds ns or equivalently 30 meters These assumptions are generally suitable for a pedestrian type of receiver network such as a group MUSTER Search space Frequency search space Code search space 1 ms correlation engine Data link based clock calibration Initialization Estimates of relative ranges and Doppler Adjustment Additional Signal Accumulation 20 ms shifts RF front end Down sampled GPS signal 1 ms signal function Estimation of signal parameters Multi platform signal accumulation Relative range correction algorithm Relative Doppler correction algorithm Biased code carrier estimates Multi platform signal accumulation Noisy unbiased code carrier estimates Kalman filter Code carrier smoothing Code carrier estimates Propagation of relative range and Doppler over time Navigation solution Communication data link 1 ms signal function 1 ms signal function 1 ms signal function Supplemental receiver 1 Supplemental receiver 2 Supplemental receiver 3 FIGURE 2 Multi platform tracking architecture for approximately known relative navigation states of cellular phone users in a shopping mall area where individual nodes stay within 100 meters from each other their relative velocities do not differ by more than 2 meters second and the clocks can be pre calibrated using communication signals In this case zero relative states are used for the multi node signal accumulation and subsequent tracking FIGURE 2 summarizes the corresponding MUSTER tracking architecture Relative navigation states are initialized based on clock calibration results only zero relative position and velocity are assumed These initial states are then propagated over time based on MUSTER supplemental tracking results Doppler frequency estimates and higher order Doppler terms Code and frequency tracking states are computed by combining biased and unbiased measurements Biased measurements are obtained by adjusting supplemental signal images for approximately known relative states only Unbiased measurements are enabled by relative range Doppler correction algorithms that estimates range and frequency adjustments for each supplemental receiver 7KH DOPDQ OWHU WKDW VXSSRUWV WKH RSWLPDO FRPELQDWLRQ of biased and unbiased tracking measurements also includes code carrier smoothing to mitigate noise in measured code phase For those cases where multiplatform signals are combined coherently a standard carrier smoothing approach is used When non coherent signal combinations are applied a so called pseudo carrier SKDVH LV UVW GHULYHG E LQWHJUDWLQJ RSSOHU HVWLPDWHV RYHU time and then applied to smooth the code phase Multi platform signal accumulation and tracking can GPS World February 2014 www gpsworld com 28