GPS, being a CDMA-based system, is severely affected by the reflections of transmitted signal, known as multipath effect. Initially GPS was proposed for aircraft, ship and vehicle navigation. In such situations, receiving a reflected signal is much less probable because of the absence of surroundings from where the signal can reflect, and ground reflections are easily blocked by the antenna. However, with applications of GPS in urban canyons and even indoors, a lot of research in the past few years has been focused on reducing the effect of multipath on the navigation solution. As a result, different algorithms have been proposed using signal processing techniques in the software. Read the rest of this entry »

The integration of GPS and INS systems has long been used to provide a robust, precise position solution for use in high accuracy applications, such as precision agriculture. The traditional method of integrating these two systems is through the use of data fusion techniques such as the Extended Kalman filter or other non-linear filtering techniques. Traditionally the GPS/INS Kalman filter is employed in either a loosely-coupled, tightly-coupled or ultra tight or deep-coupling arrangement. Read the rest of this entry »

As discussed in a previous posting, multipath remains as a largely unmitigated source of GNSS positioning error — it is a site-specific error that is difficult to model and therefore difficult to remove from multipath-corrupted GNSS range observables. This article discusses one way to at least understand multipath error, through satellite-receiver geometry. By defining some basic ideas behind the geometric relationship between the GNSS satellites, receiver, and reflecting objects, we establish the underlying principles for a class of mitigation strategies while also understanding how different factors play into multipath error. Read the rest of this entry »

Can augmenting the Kalman Filter with Artificial Intelligence increase positioning accuracy during GPS signal outages?

For land vehicle applications, in order to obtain an accurate positioning solution in denied GPS environments, low cost IMU can be integrated with GPS. Kalman Filtering (KF) was usually used to fuse the position and velocity information obtained from both systems. It benefits from the availability of the dynamic mathematical model of the INS position, velocity and attitude errors. However, KF requires stochastic models of the inertial sensor errors and a priori information about the covariances of both INS and GPS data. With low cost IMUs, it is usually difficult to come up with accurate enough stochastic models for each inertial sensor error. This may influence the KF performance and lead to large position errors, especially for low cost systems. Alternative INS/GPS integration methods, such as artificial intelligence (AI) techniques, have received more attention. The main advantage of AI over KF is that it can solve non-linear problems that map input data to output data without relying on a priori information. However, AI-based methods do not benefit from the knowledge of the dynamic model of INS errors and are in general computationally expensive.

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How geocentric are the “geocentric Cartesian coordinates” and how can they be obtained using the IGS products?

Assuming first that “geocentric Cartesian coordinates” are actually meant to be the ITRF (International Terrestrial Reference Frame) coordinates, the following holds: the ITRF coordinates are geocentric within a few cm, but not so when a mm resolution is considered, since the geocenter has both regular and irregular movements (in ITRF) of about 10 mm.

There are two possible ways how to get “geocentric” ITRF coordinates using IGS combined products:

1. Directly by using IGS orbits and clocks (the Final or Rapid) within Precise Point Positioning (PPP). This is so, since the IGS orbits/clocks, in fact, imply or provide a full realization of ITRF. Note that with IGS orbit/clock PPP one does not need any base stations or local station control, all this is in fact provided via satellites positions and clocks.
2. Using IGS orbits only and at least one nearby (preferably IGS) station, for which ITRF coordinates are known within a relative (typically double differenced) position solutions.

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Can terrestrial-based transceivers (LocataLites) be a solution to open-cut mining applications?

Acceptable RTK GNSS performance is heavily dependent on a relativity unobstructed sky-view, where there are at least five satellites with good geometry available, and on the reliability of the wireless data link used for differential corrections.

Figure 1. DeBeers Venetia Mine from East rim.

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What’s the difference between software radio, software-defined radio, and software receivers and can you give an example of a software-defined radio solution for GNSS?

Different people have different ideas about the definitions of these terms, which apply to receiver architectures. One way of defining them is as follows. First, a quick description of a classic receiver architecture. There are three basic sections of the receiver: the analogue, or RF, front end, the digital baseband section and the processor, as shown in the figure below. Software radios provide maximum design flexibility by processing the RF signal in software. This is normally achieved by digitizing the RF signal as close to the antenna as possible (using direct sampling or bandpass sampling).

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Introduction to Multipath: Why is multipath such a problem for GNSS?

Multipath is exactly what it sounds like — a signal that travels more than one path. When GNSS radio waves propagate from the GNSS satellite toward the receiving antenna, it is possible for the incoming radio signal to travel more than one path via either reflection, diffraction, or scattering.

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Significant research efforts have been made towards carrier phase ambiguity resolution (AR) and position estimation (PE) using three or more GPS or Galileo signals over the past decade. The Three Carrier Ambiguity Resolution (TCAR) and the Cascade Integer Resolution (CIR) methods described in the early literature use essentially the same geometry-free bootstrapping procedure.

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The demand for precise and reliable positioning is ever increasing in the industrial as well as in the consumer field. Industrial and commercial activities could be made more cost-effective and even new services could be launched if precise and reliable positioning would be possible for all the needs arising.

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