Recently we proposed an acquisition process for a maximum-likelihood GPS receiver that considers the joint processing of all GPS satellite waveforms. The resulting estimator was shown to provide an elegant solution to the near -far problem and to perform better than the suboptimal sliding-correlator estimator. However, the proposed acquisition model included only the code search, which estimates just the time of arrival (TOA) between a GPS satellite and a maximum-likelihood GPS receiver. In this paper we enhance the acquisition process by including the estimation of Doppler along with the estimation of the TOA, which results in a two-dimensional Doppler and code search. A maximum-likelihood GPS receiver would require only one front-end hardware section for processing all GPS signals in view, thus simplifying the entire architecture of a GPS receiver. An assessment based on theoretical performance and simulation results indicates that a maximum-likelihood GPS receiver can achieve an order-of-magnitude performance improvement relative to a sliding-correlator GPS receiver. Simulation data will be validated in the near future using GPS acquisition data from the Novatel ProPack AG-G2ϩDB9-RT2, and the results of this work will be presented in a future publication.
The signal structure performance of a direct sequence spread spectrum (DSSS) code division multiple access (CDMA) frequency division multiple access (FDMA) pseudolite indoor communication and localization (geolocation) system is presented and discussed in this paper. The signal structure of a DSSS‐FCDMA (or C‐CDMA) pseudolite indoor geolocation system appears to elegantly solve the near‐far problem when subject to a slowly varying frequency‐selective Rayleigh fading channel with additive white Gaussian noise and Doppler shift, which is the main obstacle of a DSSS‐CDMA pseudolite indoor geolocation system at roughly equal transmitter and post radio frequency (RF) receiver complexity. Based on our theoretical analysis and simulation results, it appears that FCDMA (or C‐CDMA) signal structure may be a suitable candidate for indoor geolocation to achieve 3D centimeter level position accuracy and 3D centimeter‐per‐second level velocity accuracy 99.9% of the time.
An OFDM/FDMA (or spectralized UWB) indoor geolocation system uses a profile for the configuration of the bandwidth allocation, which determines which portions of the spectrum can and cannot be allocated.
In this paper a survey of the spreading modulation of the new GPS signals (L1C, L2C, and L5) is considered. The new signals seem to offer several improvements which range from higher power, better code selection, and improved modulation schemes which offer receiver designers the opportunity to obtain unmatched performance in many ways such as in the case of a maximum likelihood GPS receiver. For example the Multiplexed Binary Offset Carrier (MBOC) spreading modulation has been recommended by the GPS-GALILEO Working Group on interoperability and compatibility because the MBOC(6,1,1/11) power spectral density is a mixture of BOC(1,1) spectrum and BOC(6,1) spectrum, that would be used by GALILEO for its Open Service (OS) signal at L1 frequency, and also by GPS for its modernized L1 Civil (L1C) signal. It is suggested that a number of different time waveforms can produce the MBOC(6,1,1/11) spectrum, allowing flexibility in implementation and maintaining interoperable waveforms for GALILEO and GPS. On the other hand, the time-multiplexed BOC (TMBOC) implementation interlaces BOC(6,1) and BOC(1,1) spreading symbols in a regular pattern, whereas composite BOC (CBOC) uses multilevel spreading symbols formed from the weighted sum of BOC(1,1) and BOC(6,1) spreading symbols, interplexed to form a constant modulus composite signal. New L1C provides a number of advanced features, which includes 75% of the power in a pilot component for enhanced signal tracking, advanced Weil-based spreading codes, an overlay code on the pilot that provides data message synchronization, support for improved reading of clock and ephemeris by combining message symbols across messages, advanced forward error control coding, and data symbol interleaving to combat fading. The resulting design offers receiver designers the opportunity to obtain a greatly improved performance in many ways. In this paper we perform a theoretical survey of the new signals and suggest a new code spreading modulation scheme which could provide even further improvements to the new GPS III signals.
The automotive and videogame industries have driven the cost of Micro-Electro-Mechanical System (MEMS) accelerometers and gyroscopes down to the range of just a few dollars. Likewise, the personal computer and cell phone industries have driven the cost of relatively high-resolution camera chips down to comparably low levels. Due to these cost reductions, a low-cost robot navigation system using a combination of vision and inertial sensors would be an inexpensive and effective method of navigating without the aid of GPS signals. Vision and inertial sensors are ideally suited to work together because their error characteristics are complementary. MEMS accelerometers and gyroscopes are capable of tracking high-speed motions, but suffer from long-term drifts that make them impractical to use as standalone navigation sensors. However, using Bayesian estimation methods, vision information from a stereo camera pair can be used to correct these drift errors. Therefore, using both vision and inertial sensors in tandem can produce an accurate navigation system that can operate indoors or in other areas where GPS signals or other navigation aids are unavailable.In this paper, we present two data analysis methods that can be used to calibrate and characterize the noise that is produced by MEMS-based IMUs.
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