HIGHLY INTEGRATED GPS, GALILEO AND INERTIAL NAVIGATION SYSTEM

• US 20100211316A1
• Filed: 05/29/2007
• Published: 08/19/2010
• Est. Priority Date: 05/29/2007
• Status: Active Grant

• Current Assignee: Deimos Engenharia S.A., Fundacio Centre Technologic de Telecomunicacions de Catalunya
• Original Assignee: Deimos Engenharia S.A., Instituto De Geomatica
• Inventors: Silva, João Simões, Diez Secadas, Jose, Fernandez Ortiz-Repiso, Antonio, Da Silva, Pedro Dias Freire, Colomina, Ismael, Caramagno, Augusto
• Granted Patent: US 8,364,401 B2
• Time in Patent Office: Days
• US Class Current: 701/216
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

Abstract

The navigation system described here utilizes GPS and Galileo satellite signals combined with Inertial Navigation Systems (INS), where a Coupled Antenna (CAN) provides both GNSS and Inertial Measurement Unit (IMU) data to a Highly Integrated GNSS-Inertial (Hi-Gi) receiver. Such receiver makes use of a high fidelity relation between GNSS unprocessed Correlator Output (COUT) I and Q data and the user trajectory, and inertial sensor data, which in turn are combined within a Kalman Filter (KF). The KF determines the navigation solution that is also used to provide feedback to the receiver demodulation signal processing stage, thus eliminating the need of dedicated structures such as Delayed Locked Loops (DLL) and Phase Locked Loops (PLL), allowing a significant improvement in navigation performance. The improvement allows this system to provide high quality measurements and operate in circumstances where usual techniques are not usable; for example during satellite signal interruption due to obstruction, or in very high dynamics or even in attenuated signal environments, due to, for example, the canopy of trees. The KF also makes use of particular Galileo signal characteristics, lock detectors and Coupled Antenna that allow the system to operate in such environments.

Claims

1. A highly integrated GPS, Galileo and inertial navigation system for enhanced navigation in low signal strength, high dynamics or other GNSS or INS harsh environments, comprising:

a Coupled Antenna (101) that provides data from the GNSS antenna and from the inertial measurement unit (IMU), where data from the first is provided to a Radio Frequency Front-End (RF-FE) and the second to the navigator, where the GNSS antenna is able to receive data from GPS and Galileo satellites and is integrated with the IMU in the same casing;

a RF-FE 102 that performs the acquisition and pre-processing of the signal transmitted by the satellite before it is passed to the phase rotation module (103);

a module (104) with a code acquisition algorithm to allow start of the tracking of the GPS and Galileo signals by providing the initial carrier phase and code;

a module (103) with a phase rotation function to allow tracking of the incoming signal'"'"'s carrier phase and frequency;

a local code generator (105) to allow generating local code replica to allow tracking of the incoming signal code phase, that is affected by different fixed delays to generate the Very-Early, Early, Prompt, Late and Very-Late replicas;

a multiplier (106) to generate a signal that will allow to correlate the local code with the incoming code;

a set (107) of integrate and dump functions to allow performing the correlation;

a data demodulator (110) to provide navigation data bits using the different local code replicas and to perform the wipe-off of such data;

a lock detector function (108) for detecting signal GNSS outages and communicate the event to a navigator (109);

a navigator (109) for determination of the navigation solution, using the GNSS data including I and Q signals when such is available and inertial sensor data to provide the necessary corrections to track the incoming GNSS signal or to keep aligned the internal local code replica during GNSS signal outages, seamlessly combined in a single filter using an accurate correlator model that relates code, phase and frequency errors, allowing the highly integrated navigation system to operate under the harsh environments;

an interface to receive navigation data from an external system, if such is available;

an interface in order to receive data from a reference station for navigation purpose, if such is available.

2. The system of claim 1, wherein the navigation solution comprises at least one of:

position, velocity and attitude.

3. The system of claim 1, wherein the integrate and dump output consist of I and Q data for Very-Early, Early, Prompt, Late and Very-Late for GNSS in general, GPS or Galileo.

4. The system of claim 1, wherein navigation data comprises at least one of:

satellite ephemeris;

corrections for GNSS signal propagation;

clock corrections;

navigation data validity information.

5. The system of claim 1 is furthermore comprised by different channels, each allocated to different satellite and frequency, having as inputs the RF-FE (102) data, where each channel included the following modules:

code acquisition (104), phase rotation (102), multipliers (106), local code generator (105), integrate and dump (I&

D) (107), lock detectors (109) and navigation data demodulator (110).

6. The navigation system of claim 1 wherein the navigator (109), further comprises:

a pre-processing function to apply corrections supplied in the navigation data that may also include functions such as smoothing of code with phase, ionospheric, tropospheric and satellite clock corrections;

a dedicated integer fix algorithm to allow solving possible integer ambiguities in the tracking of the carrier phase;

a Kalman Filter that combines the IMU and GNSS data using ultra-tight integration to determine the navigation solution as well as the carrier phase and frequency and code and estimates used in the tracking of GNSS signals.

10. The system of claim 1, wherein the lock detector comprises:

a comparator of Prompt with the output the remaining correlators to decide is signal is present, where the signal power is compared with a noise-only reference.

11. The system of claim 1, wherein the Coupled Antenna comprises:

a single case containing GNSS and IMU sensor to reduce as much possible any discrepancies that may affect tracking of the code phase and carrier phase and frequency in ultra tight coupling.

7. The system of 6, wherein the Kalman Filter module comprises:

an accurate correlator model that relates I and Q data raw measurements with code, phase and frequency error and with the position and velocity errors and that considers the integration time of the integrate and dump, discarding the need of a phase discriminator and seamlessly integrated with a set of navigation algorithms, using a code discriminator and inertial sensor data, whereby the correlator model employed provides an unique relation with receiver raw measurements of I and Q data with the actual navigation solution, providing a highly integrated navigation solution;

a code discriminator to determine the error between the estimated code and the incoming one using normalised Early and Late I and Q measurements;

a state vector comprising position errors such as, velocity, clock, attitude and inertial sensor;

a function for determination of satellite-user distance and velocity using the navigation data based on satellite ephemeris data and navigation solution, communicating results to the GNSS tracking stage.

8. The system of claim 7, wherein the KF navigation algorithms comprise:

functions for simultaneous tracking of errors of code, carrier phase and frequency with robustness to allow code only tracking even without tracking phase;

functions for prediction of the incoming carrier phase, frequency and code errors used in the prediction of I and Q data used within the Kalman Filter;

generator of partial derivatives for the carrier phase using the accurate correlator model, where each decomposition use the internal estimates of carrier phase and frequency used to control the error growth of the filter and making use of the best estimate available of the position and velocity;

generator of partial derivatives for the code carrier phase using the autocorrelation functions and the correlator error functions and using the internal estimates of code to control the error growth of the filter and making use of the best estimate available of the position and velocity.

9. The system of claim 7, wherein the accurate correlator model comprises:

exact model of the outputs of the correlators I and Q data, also termed before as correlator models, by considering the effects of the carrier phase and frequency and code errors as well as the integration time, to allow increasing integration time of GNSS signals including Galileo pilot signal and accurately relating such errors with the navigation solution, avoiding use of conventional pre-processing functions of the correlator data on the carrier phase data and allowing a highly integrated navigation solution;

technique that allows to accurately relate the correlator output I and Q data with the error of code and carrier phase and frequency and consequently with the navigation solution, within the Kalman Filter, consisting of the multiplication of two exponential modeling terms used in the prediction of I and Q data and allowing to close the loop of the navigation filter with the correlators.