We present two results on attitude estimation using vector and rate gyro measurements. The first result concerns an observer previously presented by Hamel, Mahony, and Pflimlin, with proven stability results when i) the reference vectors are stationary; or ii) the gyro measurements are unbiased. We prove semiglobal stability without either of these assumptions when a parameter projection is added, and convergence from all initial attitudes when using a resetting strategy. The second result is an algorithm for estimation of bias in the body-fixed vector measurements, which is analyzed in combination with the attitude and gyro bias observer.

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Attitude Estimation Using Biased Gyro and Vector Measurements With Time-Varying Reference Vectors

We address the issue of autonomous navigation, that is, the ability for a navigation system to provide information about the states of a vehicle without the need for a priori infrastructure such as GPS, beacons, or a map. The algorithm is known as simultaneous localisation and mapping (SLAM) and it is a terrain aided navigation system (TANS) which has the capability for online map building, and simultaneously utilising the generated map to bound the errors in the navigation solution. Since the algorithm does not require any a priori terrain information or initial knowledge of the vehicle location, it presents a powerful navigation augmentation system or more importantly, it can be implemented as an independent navigation system. Results are first provided using computer simulation which analyses the effect of the spatial density of landmarks as well as the quality of observation and inertial navigation data, and then finally the real time implementation of the algorithm on an unmanned aerial vehicle (UAV).

Autonomous airborne navigation in unknown terrain environments

Globally exponentially stable attitude and gyro bias estimation with application to GNSS/INS integration

Many applications can be envisioned for accurate, robust, and reliable navigation solution in challenging urban environments. Examples of existing and prospective applications include, but are not limited to, navigation, guidance, and control of autonomous vehicles (including both ground and aerial vehicles) for urban surveillance and reconnaissance; collection of geographical information system (GIS) data in cities; monitoring of urban infrastructure for situational awareness; and, precise automotive applications such as automated lane keeping. If used by themselves, none of the existing navigation technologies have the potential to fully satisfy the requirements for reliable and accurate navigation in urban environments. Hence, this paper develops a multi-sensor integrated solution that combines the complementary features of the Global Positioning System (GPS), laser scanner feature-based navigation, and inertial navigation for urban scenarios. GPS and laser scanner-based navigation ideally complement each other for urban navigation. The laser scanner-based navigation relies on the availability of structures (lines and surfaces) within the scan range (80 m, typically). Features (such as lines) are first extracted from laser scan images and then used for position and attitude determination. In urban areas, if there exists a building wall that blocks GPS signals, this wall creates a feature in the laser scan image. On the other hand, for open streets with limited features, the GPS signal is generally unobstructed. Thus, GPS and laser data can be combined into integrated solution architecture. The system architecture developed also exploits INS navigation states for improved solution robustness: e.g., for robust feature association between scan images and for coasting through instances where sufficient number of combined GPS/laser measurements is unavailable. A tightly coupled GPS/laser scanner/INS mechanization is developed and applied for centimeter- accurate trajectory reconstruction. The paper uses live urban data to demonstrate that combined GPS and laser scanner data generally support the observability of navigation states at any part of the urban trajectory; and, for those limited cases where insufficient GPS/laser measurements are available, the INS coasting option can be efficiently utilized. Test results presented also show that the developed tightly coupled GPS/laser scanner/INS solution provides accurate trajectory reconstruction capabilities (one sigma error residuals are at a cm-level) in challenging urban environments.

Tight coupling of GPS, laser scanner, and inertial measurements for navigation in urban environments

Global navigation satellite system (GNSS) receiver design is considered in terms of closed-loop and open-loop receiver architectures that utilize sequential and batch processing techniques. The paper uses the Global Positioning System (GPS) as a case study to demonstrate that an open-loop approach that combines batch and sequential signal processing improves GNSS signal tracking characteristics as compared to the traditionally applied closed-loop sequential receiver design for a number of important application areas. Particularly, for flight test scenarios considered, it is demonstrated that open-loop batch/sequential processing improves the GPS tracking margin by 8 dB as compared to the closed-loop sequential tracking for the case of deep GPS/Inertial Navigation System (INS) integration mode that performs code and carrier phase tracking and data bit recovery.

Chuck Bye

Papers

GPS / INS Integration