Cramer-Rao lower bound for round-trip delay ranging with subcarrier-interleaved OFDMA

IEEE Trans. Aerosp. Electron. Syst.

Staudinger

Jost

et al. 2020

Self Cite

Traditional network localization algorithms contain ranging and localization steps, which have systematic disadvantages. We propose an algorithm dubbed direct particle filter based distributed network localization (DiPNet). A node's location is directly estimated from the received signals, incorporating location uncertainty of neighboring nodes. The propagation effects on DiPNet become insignificant for dense networks, due to the massive-link collective physical layer processing. DiPNet achieves a near-optimal performance with low complexity, which is particularly attractive for realtime dense-network localization.

Section: A Simulation Resultsmentioning

confidence: 99%

Section: B Ofdm Waveform and Multipath Propagationmentioning

confidence: 99%

Distributed Direct Localization Suitable for Dense Networks

IEEE Trans. Aerosp. Electron. Syst.

Staudinger

Jost

et al. 2020

Self Cite

“…This localization requires multiple receivers or stations [28]- [30] and its performance is also highly related to the receiver-target deployment [31]. Ultra-wide bandwidth-based systems are commonly used in the localization community to obtain desirable localization performance and simple multipath mitigation without costly estimators but at the cost of a large bandwidth [32].…”

Section: A Uav Positioning and Trackingmentioning

confidence: 99%

Nonlinearity-Based Single-Channel Monopulse Tracking Method for OFDM-Aided UAV A2G Communications

Yan²,

2019

IEEE Access

Unmanned aerial vehicles (UAVs) have attracted great interest in rapid deployment for both civilian and military applications. The conventional UAV monopulse tracking technique requires dedicated pulses which suffer from multipath effect in air-to-ground (A2G) link with low elevation angles, whereas the orthogonal frequency division multiplexing (OFDM) for A2G high rate communication under frequency selective fading channel was not yet investigated for UAV target tracking at ground station. In this paper, we propose a single-channel monopulse tracking (SCMT) angle estimation method in OFDM tracking receiver exploiting square-and absolute-value nonlinear detection of amplitude-modulated difference signals. Extensive simulations are conducted to validate the proposed estimation method in terms of estimation range and estimation root mean squared error (RMSE). Results show that, the proposed angle estimation method exhibits S-shaped curve characteristic under different angle errors, which is insensitive to channels and modulations. The proposed method obtains angle estimation RMSEs smaller than 0.18 • for antenna element distance d = 0.5 m with 10 MHz OFDM signals. For both square-and absolute-value methods, a maximum degradation of 0.02 • for angle estimation RMSEs is observed under Rician channels compared with the estimation under additive white Gaussian noise (AWGN) channels, whereas the absolute-value estimation outperforms the square-value estimation. INDEX TERMSUAV target tracking, air-to-ground communication, single-channel monopulse tracking, OFDM signals, frequency selective fading channel, nonlinear detection. CHAOXING YAN received the Ph.D. degree in communication and information system from the

“…Typically, the UAVs will be equipped with a global positioning system (GPS) and an inertial measurement unit (IMU) by regulations in most countries for providing position information at any time, with a positioning accuracy ranging from 6 m to 10 m. When conventional global navigation satellite systems suffer from unacceptable vulnerabilities, such as signal occlusion, spoofing, and jamming, particularly for missioncritical operations, ranging-based localization methods offer an attractive solution to recover node location, like the multidimensional scaling (MDS) method [1], [3]. Highly accurate range measurement is also desired mostly for localization purposes in variety of commercial and military applications, such as maintaining a prescribed flight formation in swarming UAVs or munitions, localizing elements of cyber-physical systems for surveillance and exploration [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Joint Range Estimation Using Single Carrier Burst Signals for Networked UAVs

Yan²,

2021

IEEE Access

The localization accuracy demand is ever growing in UAV communication networks. We propose a joint coarse and fine range estimation method using single carrier burst signals with two samples per symbol for UAV networks. The coarse estimation of our joint estimation method exploits multiple preamble symbols for flexible single-carrier frequency-domain equalization (SC-FDE) frame structures to calculate correlation metrics, which are insensitive to frequency offset due to the differential correlation operation. Then, we propose a fine range estimation method using only two samples per symbol with expectation relying on shaping or matched filter. Furthermore, we derive the performance bounds for the ranging system using both raised cosine (RC) and better than raised-cosine (BTRC) pulses. Finally, extensive simulations are conducted to validate the proposed method in terms of estimate bias and variance for different modulations, shaping filters, and fading channels. Our simulation results show that, the root mean square errors of proposed ranging method can reach the order of centimeter at medium-to-high signal-to-noise ratio (SNR) region, whereas the case using BTRC filter is capable of enhancing the ranging performance at low SNRs.