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As radio frequency (RF) hardware continues to improve, two-way ranging (TWR) has become a viable approach for high-precision ranging applications. The precision of a TWR system is fundamentally limited by estimates of the time offset T between two platforms and the time delay τ of a signal propagating between them. In previous work, we derived a family of optimal “one-shot” joint delay–offset estimators and demonstrated that they reduce to a system of linear equations under reasonable assumptions. These estimators are simple and computationally efficient but are also susceptible to channel impairments that obstruct one or more measurements. In this work, we formulate an extended Kalman filter (EKF) for this class of estimators that specifically addresses this limitation. Unlike a generic KF approach, the proposed solution specifically integrates the estimation process to minimize the computational complexity. We benchmark the proposed first- and second-order EKF solutions against the existing one-shot estimators in a MATLAB Monte Carlo simulation environment. We demonstrate that the proposed solution achieves comparable estimation performance and, in the case of the second-order solution, reduces the computation time by an order of magnitude.

Spectral congestion and modern consumer applications motivate radio technologies that efficiently cooperate with nearby users and provide several services simultaneously. We designed and implemented a joint positioning-communications system that simultaneously enables network communications, timing synchronization, and localization to a variety of airborne and ground-based platforms. This Communications and High-Precision Positioning (CHP2) system simultaneously performs communications and precise ranging (

As radio frequency (RF) hardware continues to improve, many technologies that were traditionally impractical have suddenly become viable alternatives to legacy systems. Two-way ranging (TWR) is often considered a poor positioning solution for airborne and other vehicular navigation systems due to its low precision, poor angular resolution, and precise timing requirements. With the advent of modern RF hardware and advanced processing techniques, however, modern studies have experimentally demonstrated TWR systems with an unprecedented, sub-centimeter ranging precision with low size, weight, power, and cost (SWaP-C) consumer-grade hardware. This technique enables a new class of positioning, navigation, and timing (PNT) capabilities for urban and commercial aircraft but also instigates new system design challenges such as antenna placement, installation of new electronics, and design of supporting infrastructure. To inform these aircraft design decisions, we derive 2D and 3D Cramér–Rao lower bounds (CRLBs) on position and orientation estimation in a multi-antenna TWR system. We specifically formulate these bounds as a function of the number of antennas, platform geometry, and geometric dilution of precision (GDoP) to inform aircraft design decisions under different mission requirements. We simulate the performance of several classic position and orientation estimators in this context to validate these bounds and to graphically depict the expected performance with respect to these design considerations. To improve the accessibility of these highly theoretical results, we also present a simplified discussion of how these bounds may be applied to common airborne applications and suggest best practices for using them to inform aircraft design decisions.

Implementing new RF applications has traditionally required significant time and expertise, even for relatively simple algorithms. Software-defined radios (SDRs) have recently enabled rapid implementation and validation of RF applications without specialized hardware or advanced programming skills. We further facilitate this rapid application development by constructing WISCANet – a diverse network of commercial SDRs with specialized control software. WISCANet automatically configures these SDRs and controls transmit and receive events with minimal user input. This allows users to rapidly implement over-the-air RF applications by simply defining the baseband processing chain in software. Furthermore, WISCANet emulates real-time operations, which allows users to test real-time applications without the usual complications such as processing speed or hardware limitations. In this paper, we present recent improvements to the WISCA Software-Defined Radio Network (SDR-N). These improvements include configurable and flexible multi-channel phase coherence and support for both MATLAB and Python applications. The open source release of this software may be found on GitHub at: https://github.com/WISCA

In this paper, we present a novel unmanned aerial vehicle (UAV) radar platform to measure people’s heart rate and breathing rate from a distance. The vital drone operates as follows: fly towards the potential human targets, hover and hold its position, and then start sensing the subtle physiological motion through the onboard ultra-wideband (UWB) radar sensor. It is known that the platform motion causes the conventional radar based vital sign detection methods to fail. We propose to use an efficient data-driven method to cancel the unwanted platform fidgeting via signal-of-opportunity and to further refine the motion residual using the denoising algorithm variational model decomposition (VMD) for vital sign detection. For validation, we compare the vital sign detection performance of the UAV radar based approach against a red, green and blue color (RGB) camera based approach which is an onboard camera sensor with three-axis gimbal system for stabilization. The standard real-time pulse oximeter (PPG sensor) is used to provide the ground truth.

Limited spectral resources and increasing demand for diverse RF applications limit the capabilities of modern RF systems. Recent results in the field of RF Convergence demonstrate that these limitations may be overcome by adopting co-operative and co-design techniques. We designed the Communications and High-Precision Positioning (CHP2) system to provide positioning, navigation, and timing (PNT) and communications services in congested environments with limited spectral access. This system leverages modern two-way ranging (TWR) techniques to provide sub-centimeter ranging precision to flying ad hoc networks (FANETs) in GPS denied environments with only 10 MHz bandwidth. In this study, we extend the CHP2 TWR algorithm to improve robustness against carrier-phase range ambiguities, commonly referred to as “cycle slips”. We propose a resolution method in conjunction with joint distributed coherence and time-of-flight (ToF) tracking to mitigate these ambiguities, with a structure similar to a time-sensitive Viterbi trellis. The proposed “trellis trimming” method measures the likelihood of multiple ranging hypotheses and eliminates paths of least likeliness using Bayesian filters. We demonstrate that this method reduces the probability of incorrectly choosing range ambiguities and significantly improves ranging performance in low-SNR regimes where cycle slips are common.

Future radio systems must rely on co-existence and co-operation techniques to adapt to limited spectral resources and increasing demand. Motivated by the promise of RF Convergence co-design techniques, we designed and implemented the Communications and High-Precision Positioning (CHP2) system for flying ad hoc networks (FANETs). CHP2 simultaneously synchronizes distributed users, performs carrier-phase-accurate localization and enables network communications using limited bandwidth. We previously demonstrated rapid (

With rapid advances in flexible, software-defined computational architectures and radio front-end technologies, we have an opportunity to improve the efficiency of spectral use, reinforce system reliability, and enable new system capabilities. We deprecate the traditional “stove-piped” approach towards spectral management in favor of networks of RF, mmWave, and terahertz systems that jointly execute multiple radio functions, including communications; radar; positioning, navigation, and timing (PNT); spectral situational awareness; and opportunistic spectrum access. Such multi-function systems are enabled by a class of waveform, processing, and co-design techniques which we label spectral convergence. In this paper, we review the set of challenges obstructing the integration of such devices into the same spectral region. We briefly survey the current status of the field, outline a taxonomy of solution classes, and recommend paths towards fruitful research. We discuss existing and novel approaches towards enabling multifunction systems in the context of contemporary applications such as automotive networks and satellite meshes. We address the challenges associated with distributed resource optimization in networks of multi-function systems. We apply these concepts to a simple automotive network example and demonstrate the potential of spectral convergence solutions in a basic simulation environment

Spectral congestion limits the opportunities and performance of radio frequency (RF) systems. Spectral isolation sufficiently mitigates this congestion for a small number of users but does not offer a scalable solution once the entire spectrum is occupied. Dynamic resource management supports higher user densities by constantly renegotiating spectral access depending on need and opportunity. This approach promises efficient spectral access but is predicated on cooperation between different types of RF systems, which is a significant paradigm shift for many legacy technologies. Intelligent transportation systems (ITS) rely on several different types of RF services such as radar, communications, and positioning, navigation, and timing (PNT). RF Convergence demonstrates that many of these systems can be executed simultaneously using efficient cooperation strategies, which improves performance and limits spectral access. In this study, we demonstrate a simultaneous positioning, navigation, timing, and communications system that cooperatively executes multiple RF services. We define a "constant-information ranging" strategy that maintains constant information learned about an incoherent moving target by modulating the revisit interval to minimize the number of interactions. This significantly reduces spectral congestion and offers a control mechanism to dynamically manage spectral access. We validate the constant-information ranging algorithm in a simulation environment where we observe a 91% reduction in spectral access for a particular flight path while maintaining a 3 cm precision in ranging.

In-band, full-duplex (IBFD) radio frequency (RF) users generate self-interference that obstructs receiver operations. This interference may be mitigated using several techniques, including antenna isolation, circulators, digital mitigation, and analog mitigation at the carrier frequency. We apply an analog mitigation technique that uses a sparse tap-delay model to reduce power and computational complexity. We demonstrate that optimizing the weights of the resulting equalizer achieves sufficient self-interference mitigation, even under realistic hardware limitations. The performance is limited by i) how many delay taps are chosen, ii) how closely this discrete model matches the actual channel, iii) the dynamic range of the weighting coefficients, and iv) the timing precision of the system. We compare the achievable performance of this technique under different combinations of these limitations. We propose a sparse, constrained optimization solution that offers sufficient self-interference mitigation and significantly reduces the power consumption.

The Communications and High-Precision Positioning (CHP2) system enables secure communications and positioning services between networks of cooperative RF users. CHP2 features flexible physical and data link layers that may be tuned to prioritize communications or positioning precision to support traffic and resource management for different network conditions. We apply reinforcement learning techniques to optimize positioning performance and network throughput for a simple CHP2 network configuration. In this example, a central arbiter manages a grid of ground users tracking aerial users moving around the network. This arbiter dynamically optimizes each ground user to maximize network throughput while maintaining a minimum positioning precision on each aerial user. We demonstrate that this arbiter successfully manages the ground user resources to track the aerial targets with a minimal number of interactions. This reduces the required resources to maintain the network, which reduces the spectral congestion and power consumption for sparse networks or supports more users in congested networks.

Unmanned aerial systems (UASs) have recently enabled novel applications such as passenger transport and package delivery, but are increasingly vulnerable to cyberattack and therefore difficult to certify. These applications require robust positioning, communciations, and time synchronization services. Legacy systems such as GPS provide these capabilities extremely well, but are sensitive to spoofing and hijacking cyberattacks. In a previous study, we developed a local GPS alternative that provides highly secure communications, positioning, and timing synchronization services to networks of cooperative RF users. In this study, we consider this Communications and High-Precision Positioning (CHP2) system in the context of safety-critical transport applications and urban air mobility. We demonstrate rapid (< 100 ms) and precise (< 1cm) positioning capabilities in over-the-air experiments using flexible ground stations and UAS platforms using limited bandwidth (10 MhZ). We compare several position estimation algorithms in simulation and experimental test environments to identify suitable approaches for different applications. We discuss how the integrated communications link secures the system from spoofing and hijacking cyberattacks. We assert that the these capabilities make CHP2 a suitable candidate to provide both communications, navigation, and surveillance (CNS) and alternative positioning, navigation, and timing (APNT) services for safety-critical transport applications on a variety of vehicular platforms.

Modern RF environments are becoming increasingly congested. This limits the opportunities and capabilities of modern RF systems, obstructing the development and proliferation of new technologies. Novel vehicular RF technologies promise a new era of transportation capabilities, but legacy design techniques cannot adapt to the current spectral congestion. We summarize recent RF Convergence results and discuss how they mitigate spectral congestion in modern vehicular applications. We propose a joint radar, communications, positioning, navigation, and timing (JRCPNT) system architecture as a suitable candidate for future automotive applications. We present relevant performance bounds and initial experimental results to demonstrate the potential performance enhancements of such multiple-function RF systems. We define multiple-channel, multiple-user receiver (MCMUR) techniques that enable this architecture and discuss how these components cooperate to enable these performance enhancements. We summarize initial experimental results to demonstrate the viability of such multiple-function architectures in the context of urban air mobility (UAM) and other automotive applications.

Limited spectral access motivates radio technologies that are capable of performing multiple tasks simultaneously and efficiently cooperating with existing systems. We develop a joint positioning-communications system for a vehicular ad hoc network that simultaneously synchronizes distributed users, performs carrier-phase-accurate localization, and enables network communications. In this paper, we focus on two-way ranging methods for jointly estimating propagation delay and clock offset between the participating nodes in the network. We propose a family of novel one-shot methods to achieve distributed coherence and demonstrate that, for given conditions, such estimators reduce to a system of linear equations, hence, optimal. Here, we study the precision and computational complexity of two of these estimators using simulated flight paths and discuss their region of applicability.

Modern radio systems must adapt to limited spectral access by reducing spectrum demand and increasing operational efficiency. We design and implement a hybrid communications, navigation, and surveillance (CNS) radio system, which simultaneously performs relative positioning and network communications in a distributed network of base-stations and unmanned aerial systems (UASs). Positioning and communications tasks are performed simultaneously with a single, co-use waveform, which efficiently utilizes a limited bandwidth allocation and limits spectrum demand of new entrants. The communications task enables applications such as distributed knowledge base, air traffic management (ATM), and distributed timing synchronization, while the positioning task enables applications such as collision avoidance and automated landing. The positioning task employs a novel time-of-flight (ToF) estimation algorithm that produces high precision (σ < 5 cm) position estimates with limited bandwidth (10 MHz). The communications task provides an encrypted data link between network nodes which enables phase-accurate timing synchronization and secures the positioning system against cyberattacks such as spoofing. Multi-antenna platforms additionally enable orientation estimation and multiple-input, multiple output (MIMO) communications. We implement this system on a consumer-off-the-shelf (COTS) experimental testbed to demonstrate the functionality of the system and verify theoretical performance limits. The experimental results demonstrate that this technology is a viable alternative positioning, navigation, and timing (APNT) system which can support increasingly dense networks and numerous applications.

One solution to addressing the spectral congestion problem is to co-design communications and remote sensing systems to cooperate, such that each system benefits from the presence of one another. In this work, we present a novel joint sensing and communications multiple access system architecture that allows for simultaneous decoding of communications information and radar target tracking and parameter estimation within the same space, time, and frequency continuum. We demonstrate the feasibility of this co-design architecture by implementing it on a network of software defined radios (SDRs). To characterize the system, we consider a scenario where one transceiver transmits an emulated radar return waveform, while a second transceiver simultaneously transmits a communications waveform. A third transceiver receives and processes the emulated radar return and communications waveforms jointly. The radar transmitter and joint sensing and communications receiver acts as a quasi-monostatic tracking radar. We characterize the joint performance of the system using the communications and estimation rate metrics. The results show that the system achieves high throughput and excellent radar tracking performance for the given experiment parameters.

The growing population of radar and communications systems poses a challenge to spectral coexistence. In this preliminary study, we investigate the utility of reinforcement learning in facilitating cooperative radar and communications coexistence. We also highlight subtleties and challenges associated with employing reinforcement learning in this context. We simulate a small joint radar-communications network whose members communicate while tracking a moving target’s range. A network management system must learn how to distribute allotted bandwidth to jointly maximize communications and radar performance. Considering several constraints and assumptions in the simulation, the agent sensibly chooses actions that accomplish the required performance behavior.

Limited spectral access motivates technologies that adapt to diminishing resources and increasingly cluttered environments. We design and implement a joint positioning-communications system that enables simultaneous positioning of, and communications between, nodes in a distributed network of base-stations and unmanned aerial systems (UASs). This system design achieves high precision position estimates with fewer spectral resources than similar technologies, while simultaneously enabling orientation estimation and network communications. These capabilities are enabled by developing advanced time-of-arrival (ToA) estimators and a phase-accurate distributed coherence algorithm.

Limited spectral access motivates radar and communications technologies that can cooperate effectively. We briefly discuss the recent advancements in the fields of joint radar-communications and RF convergence to motivate a discussion of joint radar-communications network topologies. We demonstrate that MIMO spatial diversity and multi-static sensing modalities can be leveraged by a radar subsystem to massively increase effective coverage area while simultaneously providing the standard communications performance improvement. We also demonstrate that certain topologies can support a massive increase in communications user density without adversely affecting radar performance.

Radar and communications systems are often deployed in already crowded environments. The growing demand for additional communications users in frequency bands previously reserved for radar users motivates cooperation between these systems. One solution to the problem of radar-communications coexistence is to develop joint systems that simultaneously perform both tasks. One aspect of this co-design solution is to design waveforms simultaneously suitable for both systems' goals. Using a joint radar-communications waveform promises mutually beneficial performance gains while limiting spectral impact. We develop and simulate an example multiple access channel topology in which users simultaneously communicate and perform synthetic aperture radar imaging with a joint waveform. A joint radar-communications receiver is designed in the context of this example and shown to feasibly accomplish both systems' goals with a single waveform.

In this paper, the WISCA Software Defined Radio (SDR) Network platform are presented. The WISCA SDR Network provides the user with a highly configurable and flexible algorithm development platform to conduct wireless communication research. Each node in the network utilizes Ettus Research USRP (Universal Software Radio Peripheral) technology for the radio frequency front end, along with the industry standard MATLAB algorithm development environment for baseband processing. As a result, the WISCA SDR network allows the user to develop and test new concepts quickly. It demonstrates the flexibility of this system by providing a couple of examples involving message forwarding, carrier sensing and a joint radar-communications system. To help improve and further develop the system, the WISCA SDR Network will be released as an open source project.

Joint radar-communications systems attempt to address spectral congestion with cooperative spectrum sharing architectures. These architectures include co-existence, in which both systems agree to operate cooperatively, and co-design, in which both systems are designed together to achieve more efficient cooperation. We demonstrate the feasibility of a co-design architecture using a multiple-input, single-output (MISO) channel topology. This system architecture is implemented with a network of commercially available software defined radios (SDRs). The communications system uses a quadrature phase-shift keying (QPSK) modulation scheme. The radar system uses a standard linear frequency modulated (LFM) chirp. We demonstrate that a high-resolution radar return can be extracted from a simultaneous, multiple access reception using successive interference cancellation (SIC). Furthermore, we show that the high-resolution radar return can achieve similar estimation performance when compared to a radar only system.

Detection and classification of unmanned aerial vehicles (UAVs) or unmanned aerial systems (UASs) requires an understanding of their characteristics in various regimes. Two relevant UAS characteristics are measured for two consumer-grade UASs: radar cross-section (RCS) and micro-Doppler profile. RCS is measured as a function of frequency, angle, and orientation. Electromagnetic and acoustic micro-Doppler characteristics of the UASs' moving blades are also measured.

Limited spectral access motivates technologies that operate efficiently in increasingly challenging contexts. In the context of wireless communications, users compete for spectral access in already crowded environments. Managing spectrum allocation for these users, and addressing the associated challenges, is referred to as the multiple access problem. In this paper we develop a MATLAB simulation platform with which to model and simulate a variety of multiple access problems. Included within this platform is an example system implementation with airborne transceivers operating in a rich scattering environment. A multiple access receiver is designed, implemented, and evaluated in this context. Theoretical bounds on a simple multiple access problem are presented and compared to simulation results. These users are then modeled as joint radar-communications users, simultaneously communicating and conducting synthetic aperture radar (SAR) imaging using a joint radar-communications waveform. Initial SAR imaging results are presented.