This research study explores the Global Positioning System (GPS), its history, and the process of discovery needed to create the most accurate GPS possible, as well as the contemporary applications of GPS technology. Starting with the first satellite in space, GPS has been a work in progress. Originally pursued by the military for improvements to military tactics, GPS has become integrated into the everyday lives of millions of people around the world. How GPS determines location is a dichotomy, with simplistic theory and complex application. Many factors go into GPS to provide a consistent, accurate location. The orbital planes the satellites are placed in provide 24/7 coverage globally, the L-band frequencies used were chosen specifically for the characteristics they possess, and the multiple atomic clocks installed on each satellite provide incredible accuracy down to the nanoseconds, which is quintessential in GPS accuracy. The applications in GPS are far reaching and more applications are continually being discovered. With as far as GPS technology has progressed, there are still several factors that degrade the signal and are a challenge to overcome. Many of these challenges can be corrected efficiently, however, others, such as scintillation and total electron content variability in the ionosphere, create major hurdles to overcome. Luckily, there are many programs that aid in the correction process of these hurdles. The History of GPS According to R. Saunders’ article ​A Short History of GPS Development,​ The Global Positioning System (GPS) has a long history of trial and error and refinement and improvement. It’s purpose has shifted from being a military strategic asset to commonplace among the general public with its use in traveling, farming, and even banking. The beginning of GPS, introduced with a simple idea, can be traced back to the Soviet Union in the late 1950’s. In 1957, the Soviet Union made history with successfully launching the first satellite in space. To track the satellite Sputnik, Physicists and Scientists at John Hopkins University’s Applied Physics Laboratory listened to the beeps Sputnik’s signals produced. They noticed that the beeps had a Doppler Effect or Doppler Shift as the satellite passed by. Much like the sound a siren makes as a fire truck approaches, then as it passes, the sound of the siren seems different. The change in timing between the beeps let the scientist know Sputnik’s location. This led to the idea of reversing that process, to give a location on the Earth. Using radio frequencies to determine location in a two dimensional plane had been around since WWII, but using satellites would push this technology into the three dimensional realm. The United States Navy, Army, and Air Force all began developing their own GPS satellites in the 1960’s, but this was no small task. In the early 1960’s, the Navy launched its first Transit Satellite. The failure of this satellite, however, was due to

/pdf/the-global-positioning-system-30ag469ov3.pdf

The Global Positioning System

Critical government and industry sectors (such as law enforcement, transportation, communication, and finance) are growing increasingly dependent on Global Navigation Satellite Systems (GNSS) for positioning, navigation, and timing. At the same time, the availability of low-cost GNSS jamming devices are presenting a serious threat to GNSS and increasing the likelihood of outages to infrastructures relying on GNSS. The attacks range from malicious parties intentionally jamming GNSS signals within a targeted geographical region to uninformed users causing accidental interference. This paper is an overview of different approaches adopted to date to mitigate GNSS disruption caused by intentional and unintentional jamming. The first approach outlined in this paper is the use of inertial systems to aid GNSS. The second and third approaches are the filtering of jamming/interference in the spatial and time-frequency domains, respectively. The fourth approach is vector tracking of GNSS signals in the receiver.

Protecting GNSS Receivers From Jamming and Interference

This paper establishes a fundamental theory of secure clock synchronization. Accurate clock synchronization is the backbone of systems managing power distribution, financial transactions, telecommunication operations, database services, etc. Some clock synchronization (time transfer) systems, such as the global navigation satellite systems, are based on one-way communication from a master to a slave clock. Others, such as the network transport protocol, and the IEEE 1588 precision time protocol (PTP), involve two-way communication between the master and slave. This paper shows that all one-way time transfer protocols are vulnerable to replay attacks that can potentially compromise timing information. A set of conditions for secure two-way clock synchronization is proposed and proved to be necessary and sufficient. It is shown that IEEE 1588 PTP, although a two-way synchronization protocol, is not compliant with these conditions, and is therefore insecure. Requirements for secure IEEE 1588 PTP are proposed, and a second example protocol is offered to illustrate the range of compliant systems.

pdf/requirements-for-secure-clock-synchronization-wcld6ndwao.pdf

Requirements for Secure Clock Synchronization

This article discusses theoretical and practical aspects of direct position estimation (DPE) of global navigation satellite system (GNSS) receivers. DPE is an alternative approach to the well-established positioning method, where time delays and Doppler shifts to the visible satellites are estimated to solve for a geometrical problem to compute the receiver's position. In contrast, DPE infers position directly from the sampled data without intermediate steps. This approach has been seen, both theoretically and experimentally, to substantially increase the receiver's accuracy and reliability.

Direct Position Estimation of GNSS Receivers: Analyzing main results, architectures, enhancements, and challenges

Because of the recent interest in unmanned air vehicle (UAV) commercialization, there is a great need for navigation algorithms that provide accurate and robust positioning in urban environments that are often Global Positioning Systems (GPS) challenged or denied. In this paper, we present a probabilistic graph-based navigation algorithm resilient to GPS errors. Fusing GPS pseudorange and Light Detection and Ranging (LiDAR) odometry measurements with 3D building maps, we apply a batch estimation approach to generate a robust trajectory estimate and maps of the surrounding environment.We then leverage the maps to locate potential sources of GPS multipath and mitigate the effects of degraded pseudorange measurements on the trajectory estimate. We experimentally validate our results with flight tests conducted in GPS-challenged and GPS-denied environments.

Probabilistic graphical fusion of LiDAR, GPS, and 3D building maps for urban UAV navigation

Accurate, reliable, and robust global positioning system (GPS) localization is desirable for many navigation applications. Unfortunately, it is challenging for a single GPS receiver to always provide accurate positioning solutions. In urban environments, intermittent signal availability leads to degraded GPS signal tracking and position estimation of the single GPS receiver. In addition, equipment malfunction of the single GPS receiver results in inaccurate navigation solutions. This paper presents a deeply coupled multireceiver vector tracking (MRVT) architecture that improves the reliability and robustness of GPS signal tracking and position estimation. MRVT jointly tracks GPS signals received by multiple GPS receivers, mitigating GPS signal tracking disruptions, improving the reliability of GPS localization in periods of intermittent signal availability. In addition, the MRVT receiver is more robust to equipment malfunctions than the single GPS receiver. We implemented an MRVT receiver using commercial radio frequency front ends and our PyGNSS software. We experimentally validated the reliability of our MRVT receiver in periods of intermittent GPS availability experienced in downtown San Francisco. Our MRVT receiver exhibited consistent GPS signal tracking and position estimation as compared to vector tracking. In addition, we experimentally validated the robustness of our MRVT receiver to the failure of a single GPS receiver.

GNSS Multireceiver Vector Tracking

Direct GPS Positioning (DP) is a robust method that estimates the GPS navigation solution directly from the received GPS signal. In contrast, traditional methods, such as scalar tracking and vector tracking, compute intermediate channel range and range residual measurements independently, then use these as inputs into the navigation filter to estimate the navigation solution. However, a brute force implementation of DP is not computationally efficient. Our research contribution is to evaluate the robustness of DP using our more computationally efficient DP implementation. Our novel and effective DP receiver architecture initializes the navigation solution guesses as two groups: guesses varying in position and clock bias, guesses varying in velocity and clock drift. We then perform vectorized calculations to get the expected delay and Doppler between the receiver and each satellite in view. Following that, we perform batch calculations using Fast Fourier Transforms (FFTs) to obtain the vector correlation and vector spectrum. The navigation solution residual derived from the vector correlation and vector spectrum is then used as input into the navigation filter. We implemented our receiver architecture using our research platform — PyGNSS. We then evaluated the robustness of our DP receiver architecture by subjecting it to simulated jamming and meaconing attacks. We demonstrate through our experiments the robustness of our DP receiver architecture.

Mitigating jamming and meaconing attacks using direct GPS positioning

We propose Direct Position Estimation (DPE) utilizing non-line-of-sight (NLOS) GPS signals for urban navigation. In urban environments, buildings reflect GPS signals, leading to reception of NLOS GPS signals. In addition, buildings obstruct GPS signals, resulting in reduced GPS signal availability.
We treat NLOS GPS signals as additional line-of-sight (LOS) GPS signals to virtual satellites at mirror-image positions. We calculate these satellite mirror-image positions and velocities using knowledge of building reflection surfaces estimated from available three-dimensional (3D) maps. We then create expected signal receptions to include NLOS GPS signal information at multiple potential navigation candidates. Following that, we use Direct Position Estimation (DPE) to obtain the Maximum Likelihood Estimate (MLE) navigation solution. The MLE navigation solution is the navigation candidate with the expected signal reception that produced the highest overall correlation against the actual received signal.
We implemented DPE utilizing NLOS GPS signals on our software platform - PyGNSS. We conducted experiments in front of the 53 m by 40 m wind tunnel located at NASA Ames Research Center in Mountain View, California. The surface of the wind tunnel’s air intake valve is a dense metal mesh of grid size 1.8 cm, a reflector of GPS signals. We demonstrated through our experiment, an improvement in horizontal positioning accuracy by 40 m in comparison to conventional GPS positioning using scalar tracking.

Direct Position Estimation Utilizing Non-Line-of-Sight (NLOS) GPS Signals

Phasor Measurement Units (PMUs) provide time synchronized electrical measurements at many nodes across the power grid. This wide area time synchronization is made possible via GPS time transfer. Unfortunately, the GPS civilian signal is weak and vulnerable to signal interferences such as jamming and meaconing. As such, the GPS-based time synchronization of PMUs may be a potential point of entry for attacks on the power system. To address this concern, we present Direct Time Estimation (DTE) for the robust GPS-based time transfer to PMUs. As a direct method, Direct Time Estimation (DTE) does not rely on intermediate measurements such as independent channel range, range rates and their residuals. Instead, it generates the time and time drift solutions by operating directly on the raw signal. In this manner, the entire received signal information is utilized, leading to increased robustness in tracking. We developed and implemented DTE on our research platform — PyGNSS. To evaluate the performance of DTE, we conducted realistic simulations, such as jamming and meaconing, based on data collected from field experiments. Through the simulated attacks, we demonstrate the enhanced robustness of DTE with respect to conventional algorithms, such as scalar tracking.

Robust GPS-based direct time estimation for PMUs

Modern power distribution systems are incorporating Phasor Measurement Units (PMUs) to measure the instantaneous voltage and current phasors at different nodes in the power grid. These PMU devices depend on GPS for precise time and synchronization. However, GPS L1 C/A signals are vulnerable because of its low power and unencrypted signal structure. Therefore, there is a need for the development of robust time transfer techniques to ensure power grid stability.

We propose a novel multi-receiver direct time estimation (MRDTE) algorithm by utilizing the measurements from multiple receivers triggered by a common clock. We first implement a novel signal processing technique known as the Direct Time Estimation (DTE) that directly correlates the received GPS signal with the corresponding signal replica for each of the pre-generated set of clock states. The most optimal set of clock candidates is then estimated based on the principle of maximum likelihood estimation. By leveraging upon the known geographical diversity of multiple receiver positions, we employ a overall Kalman Filter to obtain a robust corrected clock bias and clock drift at any instant.

We demonstrate the increased resilience of our MRDTE algorithm against malicious timing attacks that include jamming and meaconing through outdoor field experiments.

Multi-receiver GPS-based direct time estimation for PMUs

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