arXiv subjects

José A. López-Salcedo

Publications and source records attributed to José A. López-Salcedo.

14 recordsLinked to original sources

arXiv2026

Hybrid Monostatic and Bistatic Sensing for Target Localization in OFDM Systems under Phase Noise

In hybrid monostatic-bistatic orthogonal frequency-division multiplexing (OFDM) sensing, each sensing node receives a superposition of monostatic and bistatic target returns, whose phase-noise (PN) characteristics differ fundamentally due to oscillator sharing. While monostatic sensing benefits from partial PN cancellation through the common transmit-receive oscillator, bistatic sensing involves independent oscillators and is therefore more strongly affected by PN. In this paper, we characterize the joint residual differential PN statistics of these superimposed components in a centralized two-node sensing system and quantify their impact on target localization via theoretical lower bounds considering three different receivers: (i) PN-free ideal receiver, (ii) PN-aware receiver that exploits the joint PN statistics, and (iii) PN-ignorant receiver that neglects PN.

eess.SP↗

arXiv2026

SPOC-Net: Single-Primitive Online Composition Network for GNSS Jamming Set Recognition

Reliable positioning, navigation, and timing support intelligent transportation, autonomous systems, and space-air-ground integrated networks. However, global navigation satellite system (GNSS) jamming recognizers that treat each mixture as a separate class are difficult to extend to new combinations. Therefore, this paper proposes SPOC-Net, which decomposes the recognition problem into identifying a set of basic jamming components. Multi-resolution time-frequency features and learned component queries provide evidence for each component type. A high-resolution branch estimates the number of active types, and a structured decoder combines this estimate with component evidence to select a valid set. For training, measured single-component records are the only physical samples used in gradient optimization. Their associated clean in-phase and quadrature (IQ) sequences are combined on demand during training to produce labeled mixtures with different relative powers and jamming-to-noise ratios. Separate measured mixtures from ten training-listed compositions support model selection and decoder calibration; six other compositions are reserved for final testing. Evaluation on 14,220 independently generated, conductively combined, and recorded radio frequency mixtures yields 80.69% exact-set accuracy and a 92.84% micro-averaged F1 score. On combinations excluded from model development, SPOC-Net achieves 80.89% exact-set accuracy, exceeding the strongest comparison method by 18.77 percentage points under the reported protocols.

cs.CV↗

arXiv2026

Coordination of Ground-to-Space Reference Networks for High-Precision GNSS

High-precision Global Navigation Satellite System (GNSS) services rely on accurate orbit, clock, atmospheric, and hardware-bias corrections generated from reference observations. These products are traditionally derived from terrestrial reference networks, whose performance strongly depends on the density and geographic distribution of ground stations. Consequently, sparse or regionally concentrated networks can suffer from tracking gaps and limited global observability, reducing their ability to support globally consistent high-precision products. Low Earth Orbit (LEO) constellations equipped with onboard GNSS receivers and inter-satellite links (ISLs) can serve as a network of spaceborne reference stations, offering a promising way to extend terrestrial reference networks into space, thereby improving observability for ground networks and enabling future direct correction broadcast. However, most existing network-based GNSS correction-generation workflows assume that observations can be centrally collected and processed. This assumption fails in practical ground--to--space architectures, where dynamic satellite geometry and system constraints render communication links intermittent, asymmetric, capacity-limited, and lossy. To address these limitations, this paper proposes a decentralized processing architecture that coordinates the ground-to-space GNSS reference network. By modeling ground stations and LEO satellites as interacting subnetworks over a dynamic graph, our approach allows frequent intra-tier communication while restricting cross-tier exchanges to compact estimation summaries transmitted opportunistically under probabilistic link availability....

eess.SP↗

arXiv2026

Dual-Satellite Doppler Accuracy Prediction and Geometry Selection for Sparse LEO Signals of Opportunity

Low Earth Orbit (LEO) satellites have emerged as a promising complement to GNSS for positioning in signal challenged environments. In sparse LEO signals of opportunity scenarios, Doppler positioning often relies on only one or two satellite passes, making positioning accuracy highly dependent on pass geometry. This paper investigates dual satellite LEO Doppler accuracy prediction and geometry selection. A single pass Doppler accuracy model based on the Doppler Dilution of Precision (DDOP) framework is first validated using real Iridium measurements. An information domain fusion model is then developed to combine the effective position information from two satellite passes while accounting for pass specific clock parameters. Based on this model, an analytical relationship between the intersection angle of the two predicted error ellipses and the fused positioning accuracy is derived and verified through simulations. Long term ORBCOMM observations are further used to evaluate the practical availability of favorable satellite pairs. Results show that an intersection angle of about 20° is sufficient to achieve approximately 50 m theoretical positioning accuracy, and that such complementary satellite pairs are typically available within about 30 min. These results provide practical guidance for geometry aware satellite selection and observation scheduling in sparse LEO Doppler positioning.

eess.SP↗

arXiv2026

Optimal Placement of Movable Antennas for Angle-of-Departure Estimation Under User Location Uncertainty

Movable antennas (MA) have gained significant attention in recent years to overcome the limitations of extremely large antenna arrays in terms of cost and power consumption. In this paper, we investigate the use of MA arrays at the base station (BS) for angle-of-departure (AoD) estimation under uncertainty in the user equipment (UE) location. Specifically, we (i) derive the theoretical performance limits through the Cramér-Rao bound (CRB) and (ii) optimize the antenna positions to ensure robust performance within the UE's uncertainty region. Numerical results show that dynamically optimizing antenna placement by explicitly considering the uncertainty region yields superior performance compared to fixed arrays, demonstrating the ability of MA systems to adapt and outperform conventional arrays.

eess.SP↗

arXiv2026

LEO Constellations as a Decentralized GNSS Network: Optimizing PNT Corrections in Space

With the rapid expansion of low Earth orbit (LEO) constellations, thousands of satellites are now in operation, many equipped with onboard GNSS receivers capable of continuous orbit determination and time synchronization. This development is creating an unprecedented spaceborne GNSS network, offering new opportunities for network-driven precise LEO orbit and clock estimation. Yet, current onboard GNSS processing is largely standalone and often insufficient for high-precision applications, while centralized fusion is challenging due to computational bottlenecks and the lack of in-orbit infrastructure. In this work, we report a decentralized GNSS network over large-scale LEO constellations, where each satellite processes its own measurements while exchanging compact information with neighboring nodes to enable precise orbit and time determination. We model the moving constellation as a dynamic graph and tailor a momentum-accelerated gradient tracking (GT) method to ensure steady convergence despite topology changes. Numerical simulations with constellations containing hundreds of satellites show that the proposed method matches the accuracy of an ideal centralized benchmark, while substantially reducing communication burdens. Ultimately, this framework supports the development of autonomous and self-organizing space systems, enabling high-precision navigation with reduced dependence on continuous ground contact.

eess.SP↗

arXiv2025

Theoretical and Experimental Evaluation of AoA Estimation in Single-Anchor 5G Uplink Positioning

As we move towards 6G, the demand for high-precision, cost-effective positioning solutions becomes increasingly critical. Single-anchor positioning offers a promising alternative to traditional multi-anchor approaches, particularly in complex propagation environments where infrastructure costs and deployment constraints present significant challenges. This paper provides a comprehensive evaluation of key algorithmic choices in the development of a single-anchor 5G uplink positioning testbed. Our developed testbed uses angle of arrival (AoA) estimation combined with range measurements from an ultra-wideband pair, to derive the position. The simulations conducted assess the impact of the selected algorithms on channel order and AoA estimation, while the influence of antenna calibration errors on AoA estimation is also examined. Finally, we compare simulations and results obtained from our developed platform.

eess.SP↗

arXiv2024

Angle of Arrival Estimation Using SRS in 5G NR Uplink Scenarios

This paper presents a comprehensive exploration of Angle of Arrival (AoA) estimation techniques in 5G environments, using the Sounding Reference Signal (SRS) in Uplink scenarios both in simulations and with actual measurements. Leveraging 5G capabilities, we investigate AoA algorithms for single-base station positioning. The study includes simulations and practical tests on a developed dedicated testbed featuring a base station equipped with a three-element Uniform Linear Array (ULA), considering Line of Sight conditions in an open environment. The testbed, employing Ettus E312 as the transmitter and Ettus N310 as the receiver, details waveform structures and reception processes. Additionally, our study examines the performance of Angle of Arrival (AoA) estimation algorithms, such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT), and Joint Angle and Delay Estimation (JADE) ESPRIT. A MATLAB ray tracing propagation model of the environment where the measurements are conducted, has been constructed. Simulation results using this model are presented, along with the actual measurements. The obtained results affirm the effectiveness of our implementation.

eess.SP↗

arXiv2024

USRP-Based Single Anchor Positioning: AoA with 5G Uplink Signals, and UWB Ranging

This paper presents a novel testbed designed for 5th-Generation (5G) positioning using Universal Software Radio Peripherals (USRPs). The testbed integrates multiple units: an Operation Unit for test management, a User Unit equipped with an Ettus E312 USRP, and a Station Unit featuring an Ettus N310 USRP equipped with a three-element Uniform Linear Array for Angle of Arrival estimation. Alongside ultra wideband ranging, the testbed estimates the user's position relative to the base station. Signal processing algorithms are executed in a dedicated processing unit. Key challenges addressed include phase misalignment between RX channel pairs due to different Local Oscillators in the Ettus N310, necessitating real-time calibration for precise signal alignment. High sampling rates (up to 61.44 MSps) result in large IQ sample files, managed efficiently using a snapshot technique to optimize storage without compromising testbed positioning capabilities. The testbed synchronizes angular measurements with ranging estimates allowing consistent performance evaluation for real-life cases of dynamic users (e.g. pedestrian). Experimental results demonstrate the testbed's effectiveness in achieving accurate pedestrian user localization.

eess.SP↗

arXiv2022

Semi-Assisted Signal Authentication based on Galileo ACAS

A GNSS signal authentication concept named semi-assisted authentication is proposed. It is based on the re-encryption and publication of keystream sequences of some milliseconds from an already existing encrypted signal. Some seconds after the keystreams are transmitted in the signal-in-space, the signal broadcasts the key allowing to decrypt the sequences and the a-posteriori correlation at the receiver. The concept is particularized as Galileo Assisted Commercial Authentication Service, or ACAS, for Galileo E1-B, with OSNMA used for the decryption keys, and E6C, assumed to be encrypted in the near future. This work proposes the ACAS cryptographic operations and a model for signal processing and authentication verification. Semi-assisted authentication can be provided without any modification to the signal plan of an existing GNSS, without the disclosure of signal encryption keys, and for several days of receiver autonomy, depending on its storage capabilities.

cs.CR↗

arXiv2018

Optimal Post-Detection Integration Technique for the Reacquisition of Weak GNSS Signals

This paper tackles the problem of finding the optimal non-coherent detector for the reacquisition of weak Global Navigation Satellite System (GNSS) signals in the presence of bits and phase uncertainty. Two solutions are derived based on using two detection frameworks: the Bayesian approach and the generalized likelihood ratio test (GLRT). We also derive approximate detectors of reduced computation complexity and without noticeable performance degradation. Simulation results reveal a clear improvement of the detection probability for the proposed techniques with respect to the conventional detectors implemented in high sensitivity GNSS (HS-GNSS) receivers to acquire weak GNSS signals. Finally, we draw conclusions on which is the best technique to reacquire weak GNSS signals in practice considering a trade-off between performance and complexity.

eess.SP↗

arXiv2017

Performance Bounds for Finite Moving Average Change Detection: Application to Global Navigation Satellite Systems

Due to the widespread deployment of Global Navigation Satellite Systems (GNSSs) for critical road or urban applications, one of the major challenges to be solved is the provision of integrity to terrestrial environments, so that GNSS may be safety used in these applications. To do so, the integrity of the received GNSS signal must be analyzed in order to detect some local effect disturbing the received signal. This is desirable because the presence of some local effect may cause large position errors, and hence compromise the signal integrity. Moreover, the detection of such disturbing effects must be done before some pre-established delay. This kind of detection lies within the field of transient change detection. In this work, a finite moving average stopping time is proposed in order to approach the signal integrity problem with a transient change detection framework. The statistical performance of this stopping time is investigated and compared, in the context of multipath detection, to other different methods available in the literature. Numerical results are presented in order to assess their performance.

cs.IT↗

arXiv2016

Closed-form approximations for the performance upper bound of inhomogeneous quadratic tests

This paper focuses on inhomogeneous quadratic tests, which involve the sum of a dependent non-central chi-square with a Gaussian random variable. Unfortunately, no closed-form expression is available for the statistical distribution of the resulting random variable, thus hindering the analytical characterization of these tests in terms of probability of detection and probability of false alarm. In order to circumvent this limitation, two closed-form approximations are proposed in this work based on results from Edgeworth series expansions and Extreme Value Theory (EVT). The use of these approximations is shown through a specific case of study in the context of integrity transient detection for Global Navigation Satellite Systems (GNSS). Numerical results are provided to assess the goodness of the proposed approximations, and to highlight their interest in real life applications.

stat.AP↗

arXiv2013

Maxima of Weibull-like distributions and the Lambert W function

The Weibull--like distributions form a large class of probability distributions that belong to the domain of attraction for the maxima of the Gumbel law. Besides the Weibull distribution, it includes important distributions as the Gamma laws and, in particular, the $χ^2$ distributions. In order to have explicit expressions of the norming constants for the maxima it is necessary to solve asymptotically a nonlinear equation; however, for some members of that family, numerical and simulation studies show that the constants that are usual suggested are inaccurate for moderate or even large sample sizes. In this paper we propose other norming constants computed with the asymptotics of the Lambert W function that significantly improve the accuracy of the approximation to the Gumbel law. These results are applied to the computation of the constants for the maxima of Gamma random variables that appear in some applied problems.

math.ST↗