The performance of low earth orbit (LEO) satellite Doppler positioning is fundamentally dominated by the precision with which the Doppler frequency is estimated, generally using an explicit pilot from the received signal. This letter proposes an algorithm for the precise estimation of the LEO satellite downlink Doppler frequency based on the joint use of the explicit pilot signal and an implicit pilot, which is a signal segment opportunistically available in an LEO downlink frame with all zero bits, all one bits, or interleaved zero and one bits. The theoretical performance is derived, and simulation results show that the proposed algorithm reaches the Cramer-Rao lower bound (CRLB). Verifications are conducted on signals from the Iridium mobile satellite communications system. The results show that 58.41% of Iridium frames in the ring alert and paging channels have implicit pilots and that for frames with implicit pilots, the proposed algorithm reduces the Doppler frequency estimation error by 70% compared to algorithms that use only the explicit pilot.

A symbiotic FM radio data system (SRDS) refers to a kind of digital broadcasting whose signal co-exists with the FM in channel. The SRDS signal has a symmetrical split spectrum in the band of the host FM signal spectrum. Like the FM signal, this kind of broadcasting signal also has a wide range of ground coverage. When used as an alternative to the positioning, navigation and timing (PNT), it will be meaningful for intelligent artifacts in safety-of-life applications. However, SRDS signals not only have much narrower bandwidth than GNSS signals, but also multiple peaks of auto-correlation function, which poses a serious challenge to the time of arrival (ToA) estimation. In this paper, we propose a super-resolution ToA estimation algorithm for the SRDS signals. Specifically, the properties of the auto-correlation function of SRDS signal are deduced concretely, and a two-step ToA estimation algorithm for the SRDS signal is proposed accordingly. Simulations are conducted with different configurations of quantization bits, SNR, oversampling rates and multi-path. The results show that the meter-level ranging performance can be obtained in the single-path Gaussian channel, and the ranging performance degrades from tens of meters to a hundred meters in multi-path environments.

Global navigation satellite systems (GNSSs) are used in numerous fields, but their vulnerability is a global problem that has yet to be solved. A promising way to effectively address this problem is by integrating navigation into emerging dense nongeosynchronous orbit (NGSO) megaconstellations. To maximize the downlink efficiency for users, an integrated satellite navigation and communication (ISNAC) framework is proposed in this work, in which a necessary number of packetized bursty downlink satellite communication signals are used directly for navigation purposes. Then, the user terminal estimates the time of arrival (TOA) of these ISNAC signals regardless of their coding and modulation type. To this end, a TOA estimation algorithm is proposed. Specifically, the user terminal first constructs a template signal with demodulated data bits to replicate the transmitted ISNAC signal and then calculates the cross-correlation function (CCF) of the template and the received signal for TOA estimation, based on which the TOA is finally estimated. The performance bound of the proposed TOA estimation algorithm is analyzed. Simulations are conducted to corroborate the mathematical analysis and The results show that the proposed algorithm outperforms other TOA estimators for comparsion by approaching the Cramer-Rao lower bound (CRLB) with a much lower computational complexity.

Antennas are essential components of any wireless system due to their irreplaceable functions in transmitting and receiving electromagnetic waves. Antenna radiation is based on the free electron resonance, leading to a concrete relation between its physical size and operating frequency. This fundamental principle makes it unrealizable to design well-radiated antennas with extremely small dimensions, e.g., milli-wavelength scales. Here, to overturn this commonsense correlation, an extremely miniaturization methodology of antennas is developed by integrating an arbitrary-sized antenna with an ohmic-biased transistor (OBT) circuit. In this way, we thousandfold miniaturize the antenna to an overall size at milli-wavelength scales, including the OBT circuits. Proven by the experiments in the demonstration systems, the wireless system with this thousandfold miniaturized antenna receives electromagnetic waves well. This methodology would be widely utilized in space-limited wireless systems that cannot provide enough space for antennas, benefiting various exciting areas, such as information technologies, photoelectricity physics, biomedical science, and so on.

As an alternative positioning, navigation and timing (PNT) method, integrated Doppler positioning is important in emerging direct satellite-to-phone communication and satellite-based remote Internet of Things (IoT) systems to help locate ground terminals. In this work, we offer a fundamental characterization of Doppler positioning by proposing a new scalable and analytical Doppler positioning performance bound that can be used for fast estimation of the Doppler positioning dilution in place of the legacy position dilution of precision (PDOP) expression. Then, to maximize the Doppler estimation accuracy, a Doppler estimation algorithm based on the whole signal packet is proposed, in which the Doppler rate is also considered. Finally, based on mathematical analysis, a Doppler positioning receiver architecture is proposed. Simulations are conducted with a 288-satellite Walker- $\delta ~800$ km low-Earth-orbit (LEO) satellite constellation to corroborate the mathematical analysis. The results show that the median relative error of the proposed performance bound for Doppler positioning is less than 2.5% and that the proposed Doppler estimation algorithm outperforms other Doppler estimation algorithms for Doppler positioning and approaches the Cramér-Rao lower bound (CRLB).

For unmanned air vehicles (UAVs) to survive hostile operational environments, it is always preferable to utilize all wireless positioning sources available to fuse a robust position. While belief propagation is a well-established method for all source data fusion, it is not an easy job to handle all the mathematics therein. In this work, a comprehensive mathematical framework for belief propagation-based all-source positioning of UAVs is developed, taking wireless sources including Global Navigation Satellite Systems (GNSS) space vehicles, peer UAVs, ground control stations, and signal of opportunities. Based on the mathematical framework, a positioning algorithm named Belief propagation-based Opportunistic Positioning of UAVs (BOPU) is proposed, with an unscented particle filter for Bayesian approximation. The robustness of the proposed BOPU is evaluated by a fictitious scenario that a group of formation flying UAVs encounter GNSS countermeasures en route. Four different configurations of measurements availability are simulated. The results show that the performance of BOPU varies only slightly with different measurements availability.