Algorithms for GPS operation indoors and downtown

Agarwal, N.; Basch, Julien; Beckmann, Paul J.; Bharti, Piyush; Bloebaum, Scott; Casadei, Stefano; Chou, Andrew; Enge, Per; Fong, Wungkum; Hathi, Neesha; Mann, Wallace; Sahai, Anant; Stone, Jesse; Tsitsiklis, John N.; Roy, Benjamin Van

doi:10.1007/s10291-002-0028-0

Cited by 55 publications

(23 citation statements)

References 8 publications

(5 reference statements)

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“…When satellite signals are partially blocked or shaded, the signal strengths may be in the −150 dBm range, and such signals are considered weak. To acquire weak signals, more input data are necessary to perform a coherent or noncoherent integration operation to enhance the signal-tonoise ratio (SNR) [14,15]. A more general scenario is that signals from different satellites vary in strengths, with some in the −130 dBm range and others in the −150 dBm range or even lower.…”

Section: Introductionmentioning

confidence: 99%

Fast GNSS satellite signal acquisition method based on multiple resamplings

Wang

Mao

2016

EURASIP J. Adv. Signal Process.

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A fast Global Navigation Satellite System (GNSS) satellite signal acquisition method based on resampling is presented. In contrast to traditional approaches, which perform a single-round search with a high data rate, the proposed method introduces a signal acquisition mechanism that uses data resampling. Starting from a resampled data rate slightly above the Nyquist frequency, the proposed method conducts multiple rounds of searches with an increasing sampling rate. After each round of searching, the satellites are sorted according to their relative signal strengths. By removing satellites at the bottom of each sorted list, the search space for satellite acquisition is continuously pruned. If a sufficient number of satellites are not acquired when the original data rate is reached, the method will switch to the weak-signal detection mode and use non-coherent integration for the satellites at the top on the list. The non-coherent integration process continues until either a sufficient number of satellites are acquired or the maximum number of steps is reached. The experimental results show that the proposed method can acquire the same set of satellites as traditional methods but with a considerably lower computational cost. The proposed method was implemented in a software-based GNSS receiver and can also be used in hardware-based receivers.

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Section: Introductionmentioning

confidence: 99%

Fast GNSS satellite signal acquisition method based on multiple resamplings

Wang

Mao

2016

EURASIP J. Adv. Signal Process.

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“…But it takes about fifteen seconds to accomplish bit and frame synchronization by message, and receivers can not locate before frame synchronization completed. Through auxiliary methods [2,3], before frame synchronization, receivers can recover the milliseconds of the signal emission to accelerate TTFF.…”

Section: Introductionmentioning

confidence: 99%

A Quick Location Method for High Dynamic GNSS Receiver Based on Time Assistance

Ping

Jing

Liu

et al. 2013

INT J COMPUT COMMUN

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Traditional A-GPS positioning method when quickly calculate a position, need a condition that the approximate position must not exceed 150km, otherwise the calculation will be very complex. This paper proposes a time-assisted fast positioning method for high dynamic GNSS receiver, effectively solving the problem of large search calculation in traditional method, even if exact position is unknown after the signal is recaptured. According to the known auxiliary time information and implied elevation information, this paper put forwards a custom coordinate system for building twodimensional search space, which could reduce the number of search-dimensions. It proposes a search method based on receiver clock calculated by analyzing the influence of time auxiliary accuracy. By using GPS ephemeris data provided by the IGS, it builds a simulation environment and analyzes the influence of different preferred satellites based on the custom coordinate system on the calculation, and thus puts forward a principle for choosing the preferred satellites. Simulation examples show that through the rational combination of satellites to create a custom coordinate system, and when time auxiliary accuracy is less than 60us, the calculation can 100% guarantee to restore a complete satellite signal emission time and obtain an accurate position.

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“…If N is large this may not suffice. For example in applications to GPS [1], as in Problem I-A.1 above, we have N ≥ 1000. This leads to the following:…”

Section: E the Fast Matched Filter (Fmf) Problemmentioning

confidence: 99%

“…Hence, the client receives the sequence R ∈ H of the form where α 0 ∈ C is the complex amplitude, with |α 0 | ≤ 1, ω 0 ∈ Z N encodes the radial velocity of the satellite with respect to the client, τ 0 ∈ Z N encodes the distance between the satellite and the client 2 , and W is a random white noise 3 . The problem of GPS 1 We denote i = √ −1. 2 Using τ 0 we can compute [12] the distance from the satellite to the client, assuming a line of sight between them.…”

Section: A Example: the Gps Problemmentioning

confidence: 99%

Delay-Doppler Channel Estimation in Almost Linear Complexity

Fish

Gurevich²,

Hadani

et al. 2013

IEEE Trans. Inform. Theory

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Abstract-A fundamental task in wireless communication is channel estimation: Compute the channel parameters a signal undergoes while traveling from a transmitter to a receiver. In the case of delay-Doppler channel, a widely used method is the matched filter algorithm. It uses a pseudo-random sequence of length N, and, in case of non-trivial relative velocity between transmitter and receiver, its computational complexity is O(N 2 log N ). In this paper we introduce a novel approach of designing sequences that allow faster channel estimation. Using group representation techniques we construct sequences, which enable us to introduce a new algorithm, called the flag method, that significantly improves the matched filter algorithm. The flag method finds the channel parameters in O(m · N log N ) operations, for channel of sparsity m. We discuss applications of the flag method to GPS, radar system, and mobile communication as well.

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Algorithms for GPS operation indoors and downtown

Cited by 55 publications

References 8 publications

Fast GNSS satellite signal acquisition method based on multiple resamplings

Fast GNSS satellite signal acquisition method based on multiple resamplings

A Quick Location Method for High Dynamic GNSS Receiver Based on Time Assistance

Delay-Doppler Channel Estimation in Almost Linear Complexity

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