Design & Test

Innovation: Mobile-Phone GPS Antennas

February 1, 2010By
Figure 4. Sarantel miniature volute antenna

Can They Be Better?
We examine the antenna designs that provide GPS functionality to mobile phones and why most phones still do not provide GPS operation indoors. We also see what it will take to make them better. read more

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Multi-Sensor, Multi-Network Positioning

February 1, 2010By
FIGURE 1. Sample WLAN or Bluetooth fingerprint map, in meters.

Currently, no single technology, system, or sensor can provide a positioning solution any time, anywhere. The key is to utilize multiple technologies. We are now exploring a multi-sensor multi-network (MSMN) approach for a seamless indoor-outdoor solution. Its hardware platform is described in the previous article. The digital signal processor (DSP) is embedded in the GPS module. All sensors are integrated to the DSP that hosts core software for real-time sensor data acquisition and real-time processing to estimate user location. A smartphone handset provides wireless network measurements. read more

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Innovation: Collective Detection

January 1, 2010By
I-T

Enhancing GNSS Receiver Sensitivity by Combining Signals from Multiple Satellites
A new approach to enhancing signal sensitivity combines the received signal power from multiple satellites in a direct-to-navigation solution. read more

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Testing Software Receivers

December 1, 2009By

To meet the challenges inherent in producing a low-cost, highly CPU-efficient software receiver, the multiple offset post-processing method leverages the unique features of software GNSS receivers to greatly improve the coverage and statistical validity of receiver testing compared to traditional, hardware-based testing setups, in some cases by an order of magnitude or more. read more

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The Smartphone Revolution

December 1, 2009By
SmartPhones

Seven technologies put GPS in mobile phones around the world. Here is the how and why of location’s entry into modern consumer mobile communications. read more

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On the Edge: Multipath Measures Snow Depth

November 1, 2009By
FIGURE 2. Snow depth derived from GPS (red squares), the three ultrasonic snow depth sensors (blue lines), and field measurements (black diamonds). Bars on field observations are one standard deviation. GPS snow-depth estimates during the first storm (doy 85.5–86.5) are not shown (gray region) because the SNR data indicate that snow was on top of the antenna.

The September “Innovation” column in this magazine, “It’s Not All Bad: Understanding and Using GNSS Multipath,” by Andria Bilich and Kristine Larson (see www.gpsworld.com/multipath), mentions the use of multipath in studying soil moisture, ocean altimetry and winds, and snow sensing. An experiment the authors conducted, designed to study soil moisture, yielded a surprise bonus: a new methodology for measuring snow depth via GPS multipath. It has important implications for weather and flood forecasting, and could also bring new insight to bear on GPS antenna design. read more

Higher Timing Accuracy, Lower Cost

November 1, 2009By
AURORA BOREALIS seen from Churchill, Manitoba, Canada. Ionospheric scintillation research can benefit from this new method.

Inside a typical GNSS receiver, the estimate of the error in the local oscillator is formed as a component of the navigation solution, which is in turn based on the output of each satellite-tracking channel propagating its estimate of carrier and code measurements to a common future point. But this method limits the resolution with which the noise of the local oscillator can be quantified. To bypass this shortcoming requires a method of coherently gathering information about the phase change in the local oscillator across all available satellite signals: to use the same samples simultaneously for all satellites in view to estimate the center-point phase error common across the visible constellation. We explore how. read more

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Innovation: Improving Dilution of Precision

November 1, 2009By
Inn-T

A Companion Measure of Systematic Effects
GPS receivers must deal with measurements and models that have some degree of error, which gets propagated into the position solution. If the errors are systematically different for the different simultaneous pseudoranges, as is typically the case when trying to correct for ionospheric and tropospheric effects, these errors propagate into the receiver solution in a way that is fundamentally different from the way that random errors propagate. So in addition to dilution of precision, we need a companion measure of systematic effects. In this month’s column, we introduce just such a measure. read more

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