I Hear, Therefore I Know Where I Am: Compensating for GNSS Limitations with Cellular Signals

Abstract

G lobal navigation satellite systems (GNSSs) have been the prevalent positioning, navigation, and timing technology over the past few decades. However, GNSS signals suffer from four main limitations: 1) They are extremely weak and unusable in certain environments (e.g., indoors and deep urban canyons) [1]. 2) They are susceptible to unintentional interference and intentional jamming [2], [3]. 3) Civilian signals are unencrypted, unauthenticated, and specified in publicly available documents, making them spoofable (i.e., hackable) [3]. 4) Their position estimate suffers from a large vertical estimation uncertainty due to the lack of GNSS space vehicle (SV) angle diversity, which is particularly problematic for aerial vehicles [4]. As such, standalone GNSSs will not deliver the stringent demands of future systems such as autonomous vehicles, intelligent transportation systems, and location-based services. Research over the past few years has revealed the potential of signals of opportunity as an alternative or a complement to GNSSs. Signals of opportunity are ambient signals not intended for positioning, navigation, and timing, such as cellular, AM/FM radio, satellite communication, digital television, and Wi-Fi. Among these signals, cellular signals are particularly attractive due to their abundance, geometric diversity, high carrier frequency, large bandwidth, and high received power. This article presents a multisignal software-defined receiver (SDR) architecture for navigating with cellular code division multiple access (CDMA) and long-term evolution (LTE) signals. When GNSS signals are unavailable or compromised, the SDR extracts navigation observables from cellular signals, producing a navigation solution in a standalone fashion. When GNSS signals are available, the cellular navigation observables are fused with GNSS observables, yielding a superior navigation solution to a standalone GNSS solution. Exploiting the abundant cellular signals in the environment provides a more robust and accurate navigation solution.

LTE receiver design and multipath analysis for navigation in urban environments

“…which is decreased by a factor of I compared with (17). Since the CRS is transmitted on multiple symbols in a frame, it is possible to take the average over the symbols carrying the CRS in only one frame while keeping the DLL loop update time equal to a frame duration.…”

“…It exploits ambient signals of opportunity (SOPs), such as cellular, digital television, AM/FM, WiFi, and iridium satellite signals . Among the different SOPs, cellular signals are particularly attractive due to their ubiquity, geometric diversity, high received power, and large bandwidth . Cellular signals can be exploited for localization either to produce a navigation solution in a standalone fashion or to aid the INS in the absence of GNSS signals .…”

“…The positioning performance achieved with LTE signals has been analyzed in the literature, andseveral software‐defined receivers (SDRs) have been proposed for navigation with real and laboratory‐emulated LTE signals . Experimental results demonstrated navigation solutions with different types of LTE reference signals in different environments, achieving meter‐level accuracy …”

“…[9][10][11][12][13][14][15][16] Among the different SOPs, cellular signals are particularly attractive due to their ubiquity, geometric diversity, high received power, and large bandwidth. 17 Cellular signals can be exploited for localization either to produce a navigation solution in a standalone fashion 18,19 or to aid the INS in the absence of GNSS signals. 20 Moreover, it has been demonstrated that fusing cellular signals with GNSS signals, when available, significantly improves the positioning accuracy.…”

“…[28][29][30] Experimental results demonstrated navigation solutions with different types of LTE reference signals in different environments, achieving meter-level accuracy. 17,23,[30][31][32] Five reference sequences in the received LTE signal have been studied for positioning: primary synchronization signal (PSS), secondary synchronization signal (SSS), cell-specific reference signal (CRS), positioning reference signal (PRS), and cyclic prefix (CP). Among these sequences, it was demonstrated that the CRS is always available and yields the most precise positioning due to its large transmission bandwidth.…”