New Methods for MLE of Toeplitz Structured Covariance Matrices with Applications to RADAR Problems

This work considers Maximum Likelihood Estimation (MLE) of a Toeplitz structured covariance matrix. In this regard, an equivalent reformulation of the MLE problem is introduced and two iterative algorithms are proposed for the optimization of the equivalent statistical learning framework. Both the strategies are based on the Majorization Minimization (MM) paradigm and hence enjoy nice properties such as monotonicity and ensured convergence to a stationary point of the equivalent MLE problem. The proposed framework is also extended to deal with MLE of other practically relevant covariance structures, namely, the banded Toeplitz, block Toeplitz, and Toeplitz-block-Toeplitz. Through numerical simulations, it is shown that the new methods provide excellent performance levels in terms of both mean square estimation error (which is very close to the benchmark Cram\'er-Rao Bound (CRB)) and signal-to-interference-plus-noise ratio, especially in comparison with state of the art strategies.Comment: submitted to IEEE Transactions on Signal Processing. arXiv admin note: substantial text overlap with arXiv:2110.1217

Re-determination of the primary shelf-life of food products: what are the guarantees for the consumer?

Except in rare cases, the determination of the shelf-life of food products is left up to the food business operator. The extension of this period, which for years has been the subject of debate among the various actors in the food chain, has become a topic of fundamental importance also following the recent economic/financial, environmental, and health crises, which have had an inevitable impact on consumption and food waste. While there is no requirement to indicate durability for some categories of food products, for example, those not directly intended for consumers, this debate has raised questions and perplexities about the potential reevaluation of the origin conditions established by the manufacturer, particularly when it comes to maintaining the guarantees for the consumer in terms of health and hygiene. In addition, the increasing consumer demand for accurate information has prompted the European authorities to request a public consultation on the actual understanding and perception of the mandatory terms on labels such as use by or date of minimum durability of a food, provided for by Article 9 of Regulation (EU) No. 1169/2011, often not correctly understood, which can assume great significance in the application of rules to reduce food waste. In this regard, it is useful to remember that the recent measures adopted by the European Union legislator, together with the case law of recent years, have led the judges of merit to comply with the principles and requirements of food safety laid down since 2002 in Regulation (EC) No. 178, thus paying greater attention to the analysis, assessment, and management of the risk of the entire production chain. The purpose of this work is to provide technical-legal elements to encourage a possible extension of the shelf-life of food products while ensuring the safety of consumers

Radar detection performance prediction using measured UAVs RCS data

This paper presents measurements of Radar Cross Section (RCS) of five Unmanned Aerial Vehicles (UAVs), comprising both consumer grade and professional small drones, collected in a semi-controlled environment as a function of azimuth aspect angle, polarization and frequency in the range 8.2-18 GHz. The experimental setup and the data pre-processing, which include coherent background subtraction and range gating procedures, are illustrated in detail. Furthermore, a thorough description of the calibration process, which is based on the substitution method, is discussed. Then, a first-order statistical analysis of the measured RCSs is provided by means of the Cramér-von Mises (CVM) distance and the Kolmogorov-Smirnov (KS) test. Finally, radar detection performance is assessed on both measured and bespoke simulated data (leveraging the results of the developed statistical analysis), including, as benchmark terms, the curves for non-fluctuating and Rayleigh fluctuating targets

Radar detection performance via frequency agility using measured UAVs RCS data

This paper addresses radar detection performance prediction (via measured data) for drone targets using a frequency agility-based incoherent (square-law) detector. To this end, a preliminary statistical analysis of the integrated Radar Cross Section (RCS) resulting from frequency agile pulses is carried out for drones of different sizes and characteristics, using data acquired in a semi-controlled environment for distinct frequencies, angles, and polarizations. The analysis involves fitting the integrated RCS measurements with commonly used one-parametric and two-parametric probability distributions and leverages the Cramér-von Mises distance and the Kolmogorov Smirnov test. Results show that the Gamma distribution appears to accurately model the resulting fluctuations. Hence, the impact of integration and frequency agility on the RCS fluctuation dispersion is studied. Finally, detection performance of the incoherent square-law detector is assessed for different target and radar parameters, using both measured and simulated data drawn from a Gamma distribution whose parameters follow the preliminary RCS statistical analysis. The results highlight a good agreement between simulated and measurement-based curves

Performance prediction of the coherent radar detector on measured UAVs data

This paper presents measurements of Radar Cross Section (RCS) of five Unmanned Aerial Vehicles (UAVs), comprising both consumer grade and professional small drones, collected in a semi-controlled environment as a function of azimuth aspect angle, polarization and frequency in the range 8.2-18 GHz. A first-order statistical analysis of the measured RCSs is firstly reported prior to assessing the radar detection performance on both measured and bespoke simulated data (leveraging the results of the developed statistical analysis), including, as benchmark terms, the curves for non-fluctuating and Rayleigh fluctuating targets

RCS measurements of UAVs and their statistical analysis

This paper deals with Radar Cross Section (RCS) measurements of five small Unmanned Aerial Vehicles (UAVs) in a semi-controlled environment as a function of azimuth aspect angle, polarization, and frequency in the range 8.2-18 GHz. The experimental setup and the data pre-processing, which include coherent background subtraction, range gating procedures, and calibration, are presented. Then, a thorough statistical analysis of the measured RCSs is provided by means of the Cram´er–von Mises (CVM) distance and the Kolmogorov–Smirnov (KS) test