When the reception of GPS signals becomes unreliable, an alternative is to explore signals of opportunity (SOOP) for positioning. Broadcast digital radio transmissions (e.g., digital TV signals) contain field and segment sync codes, which can be used for ranging even though it was not originally designed for so. Another example is the wireless local area network (WLAN) signals. However, there are two major difficulties. Although the location of SOOP sources is known, the number of independent SOOP sources and their geometric distribution may not be favorable for precise positioning. Besides, the clocks of SOOP transmitters are not synchronized, each subject to a different bias and drift. To respond to the 2009 NAECON Grand Challenge, we set forth a cooperative position location approach. The proposed concept makes use of differential ranges between cooperative devices to a common SOOP source, the relative ranges between the cooperative devices, and displacement measurements by the cooperative devices. The cooperation among networked location devices not only allows them to choose the most appropriate positioning mechanism but also provides them with additional measurements to reduce the number of SOOP otherwise required. In addition to data exchange, the radio link between two cooperative devices also allows for estimation of their clock offset. This leads to a joint position location solution via fixedpoint smoothing. In this paper, we present the proposed system concept, its subsystems, and their operations and also analyze preliminary simulation results.
In Global Positioning System (GPS)-challenged environments, broadcast and wireless communications signals are used as alternatives via fingerprinting or trilateration for positioning and navigation. In trilateration, the time of flight of recognizable patterns of a signal of opportunity (SOOP) is determined from the time of departure (TOD) from its source and the time of arrival at a user. However, most SOOPs are neither synchronous nor cooperative. There is a need to deal with the unknown TOD. In this paper, relative ranges are generated from radio signals by time difference with respect to an initial known point (thus removing TOD) to enable relative positioning from the known initial point. The paper also considers a critical aspect of maintaining continuous tracking of signals of opportunity in the presence of mobile fading. To demonstrate, we built mobile testbeds and conducted field tests, which are presented in this paper together with an analysis of the results.
ABSTRACT:The symmetric phase-only matched filter (SPOMF) is studied in this paper for processing GPS signals. The use of phase-only information is equivalent to equalizing the magnitude spectrum in contrast to the original spectrum that tapers off according to a sinc-function. This tends to accentuate the high frequency components corresponding to edges or transitions in the signals. As such, the SPOMF produces a much sharper peak (ideally a Dirac delta function) that is more accurate in timing and less sensitive to multipath. In addition, the same operation is applicable to both a binary phase shift keying (BPSK) modulated signal such as the GPS C/A-code and P(Y)-code and a binary offset carrier (BOC) modulation such as the GPS M-code and Galileo codes. More importantly, it only produces a single matching peak regardless of which modulation code is used.
INTRODUCTIONGPS is a space-based satellite radio navigation system that provides three-dimensional (3-D) user positioning by solving a set of nonlinear trilateration equations using pseudorange measurements. The current method of solving the nonlinear equations is to linearize the pseudorange equations and calculate the user position iteratively, starting with a user-provided initial position estimate [1]. For near-earth navigation, the center of the earth is a good initial estimate, and the currently used iterative least-squares (ILS) algorithm converges to the GPS solution. An area of potential improvement that has been investigated in recent years is the use of noniterative closed-form solutions to the nonlinear pseudorange GPS equations. Closed-form solutions have been developed in [2 -9]. This paper improves on [8] and [9] by employing a more rigorous mathematical formulation. In this paper and in our previous work [8,9], an overdetermined system is treated, making use of all-in-view (n Ͼ 5) satellites as opposed to using just 4 satellites. Moreover, this work departs from a deterministic formulation of the problem [2,4,6,7] and specifically addresses the development of a reliable closed-form solution that works in the presence of measurement noise. Previous work, with the exception of [10], treated the pseudorange equations as a deterministic set of equations. In [11], the deterministic solution of [2] is adapted to account for measurement noise, and this approach is further developed in [12].In this paper, it is recognized up front that pseudorange measurements are noise corrupted. Hence, the stochastic nature of the measurements is reflected in the GPS pseudorange equations from the outset to develop a probabilistically sound GPS solution. By stochastically modeling the measurement situation at hand, solving for position becomes a stochastic estimation problem. The use of correct stochastic modeling and estimation yields a GPS solution that, in addition to the position estimate, provides an estimate of the measurement noise intensity, provided there are more than 5 satellites in view.Thus, the estimation algorithm developed here provides a data-driven position (and user clock bias) estimation error covariance prediction. This prediction introduces a new confidence factor into GPS positioning that is critical for the downstream integration of GPS and inertial navigation systems (INS) or synthetic aperture radar (SAR) sensors. Moreover, an attractive feature of our solution is its good estimation performance, achieved even under high geometric dilution of precision (GDOP) conditions and in urban environments where the number of visible satellites is reduced to 4.Moreover, a direct, or autonomous, solution that does not require an initial position estimate is attractive for space navigation and for unusual planar array configurations using pseudolites, where the iterative process is sensitive to the initial position estimate (e.g., the application discussed in [13] and [14]
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