Industrial policies in Europe: an introduction

As guest editors of this Special Issue of PE/JEP we have selected a small number of rather detailed assessment of contemporary history of domestic industrial policies in the international context. The four papers included in this Special Issue can be seen as three case studies of “sectoral” innovation policies (broad band, wind energy, biotechnology) with a strong emphasis on country institutional features and policy instruments, together with one “horizontal” case of industrial policy in a specific country context (innovative startups in Italy). The heterogeneous theoretical background (industrial organization, evolutionary theory of the firm, economics of innovation, development) provides a somewhat unifying hidden thread of these case studies, without becoming a subject of analysis per se. This approach has been our intentional editorial choice and we are fully aware of its limitations. After very short non-technical summaries of the four papers (Section 1) we try to present a rather synthetic assessment of our personal views (largely shared among us even with partial minor disagreements) about the increasingly hot debate on the nature, limitations and desirable perspectives of industrial policy today. We argue for a non-ideological forward-looking role of governments as active players in helping domestic entrepreneurial resources not only to fully exploit inherited comparative advantages but also to face structural uncertainties and discover own potential competitive advantages in a rapidly changing international context (Section 2)

On the Use of a Two-Dimensional Cyclic Prefix in OTFS Modulation and Its Implications

In this manuscript we investigate the implications of adopting a double cyclic prefix in the orthogonal time-frequency space modulation. Our study first focuses on the analysis of the modulated signal and on the development of a useful model for the received signal in the presence of a doubly selective fading channel. On the one hand, our mathematical results allow us to accurately assess the impact of pulse shaping on the structure of the transmitted waveform and on its power spectral density, and to develop some simple rules for allocating multiple pilot symbols within each orthogonal time-frequency space symbol. On the other hand, they are exploited to develop a novel algorithm for pilot-aided channel estimation, whose output provides a detailed representation of the communication channel; for this reason, it can be used for sensing at the transmit side in integrated sensing and communication applications, or for channel equalization at the receive side in digital communications. Our numerical results evidence that our channel estimation & equalization algorithm outperforms the other related techniques available in the technical literature at the price of a limited increase in computational complexity

A Novel Method for the Computation of the Deterministic Maximum Likelihood Estimator of Multiple Real Sinusoids

In this manuscript a novel computationally efficient method for implementing the Deter- ministic Maximum Likelihood estimator of multiple superimposed real sinusoids is derived. This method is an adaptation of a recently proposed algorithm for the estimation of undamped exponentials and offers two significant advantages in terms of complexity with respect to various alternatives available in the technical literature. First, the dependence of the computational complexity on the snapshot length is the same as that of the Fast Fourier Transform. Consequently, increasing the snapshot length does not have a substantial impact on the overall computational burden. Second, the proposed method exploits the ability of the periodogram estimator to coarsely locate the global maximum of the Deterministic Maximum Likelihood cost function, thereby eliminating the need for a global search on this last function. Our numerical results show that it achieves a better accuracy-complexity trade-off than various estimators available in the literature

Novel Deterministic Detection and Estimation Algorithms for Colocated Multiple-Input Multiple-Output Radars

In this manuscript, the problem of detecting multiple targets and estimating their spatial coordinates (namely, their range and the direction of arrival of their electromagnetic echoes) in a colocated multiple-input multiple-output radar system operating in a static or slowly changing two-dimensional or three-dimensional propagation scenario is investigated. Various solutions, collectively called range & angle serial cancellation algorithms, are developed for both frequency modulated continuous wave radars and stepped frequency continuous wave radars. Moreover, specific technical problems experienced in their implementation are discussed. Finally, the accuracy achieved by these algorithms in the presence of multiple targets is assessed on the basis of both synthetically generated data and of the measurements acquired through three different multiple-input multiple-output radars and is compared with that provided by other methods based on multidimensional Fourier analysis and multiple signal classification

Deterministic Algorithms for Four-Dimensional Imaging in Colocated MIMO OFDM-Based Radar Systems

In this manuscript, the problem of detecting multiple targets and jointly estimating their spatial coordinates (namely, the range, the Doppler and the direction of arrival of their electromagnetic echoes) in a colocated multiple-input multiple-output radar system employing orthogonal frequency division multiplexing is investigated. It is well known its optimal solution, namely the joint maximum likelihood estimator of an unknown number of targets, is unfeasible because of its huge computational complexity. Moreover, until now, sub-optimal solutions have not been proposed in the technical literature. In this manuscript a novel approach to the development of reduced complexity solutions is illustrated. It is based on the idea of separating angle estimation from range-Doppler estimation, and of exploiting known algorithms for solving these two sub-problems. A detailed analysis of the accuracy and complexity of various detection and estimation methods based on this approach is provided. Our numerical results evidence that one of these methods is able to approach optimal performance in the maximum likelihood sense with a limited computational effort in different scenarios

An Approximate Maximum Likelihood Method for the Joint Estimation of Range and Doppler of Multiple Targets in OFDM-Based Radar Systems

In this manuscript, an innovative method for the detection and the estimation of multiple targets in a radar system employing orthogonal frequency division multiplexing is illustrated. The core of this method is represented by a novel algorithm for detecting multiple superimposed two-dimensional complex tones in the presence of noise and estimating their parameters. This algorithm is based on a maximum likelihood approach and combines a single tone estimator with a serial cancellation procedure. Our numerical results lead to the conclusion that the developed method can achieve a substantially better accuracy-complexity trade-off than various related techniques in the presence of closely spaced targets

Deterministic Signal Processing Techniques for OFDM-Based Radar Sensing: An Overview

In this manuscript, we analyze the most relevant classes of deterministic signal processing methods currently available for the detection and the estimation of multiple targets in a joint communication and sensing system employing orthogonal frequency division multiplexing. Our objective is offering a fair comparison of the available technical options in terms of required computational complexity and accuracy in both range and Doppler estimation. Our numerical results, obtained in various scenarios, evidence that distinct algorithms can achieve a substantially different accuracy-complexity trade-off

Noise reduction in muon tomography for detecting high density objects

The muon tomography technique, based on multiple Coulomb scattering of cosmic ray muons, has been proposed as a tool to detect the presence of high density objects inside closed volumes. In this paper a new and innovative method is presented to handle the density fluctuations (noise) of reconstructed images, a well known problem of this technique. The effectiveness of our method is evaluated using experimental data obtained with a muon tomography prototype located at the Legnaro National Laboratories (LNL) of the Istituto Nazionale di Fisica Nucleare (INFN). The results reported in this paper, obtained with real cosmic ray data, show that with appropriate image filtering and muon momentum classification, the muon tomography technique can detect high density materials, such as lead, albeit surrounded by light or medium density material, in short times. A comparison with algorithms published in literature is also presented

Special nuclear material detection studies with the SMANDRA mobile system

The detection of special nuclear material has been studied with the SMANDRA mobile inspection system used both as a high sensitivity passive neutron/gamma spectroscopic tool and as an active inspection device using tagged neutrons. The detection of plutonium samples is possible with passive interrogation, the passive detection of uranium being much more difficult because of the low neutron yield and of the easiness of shielding the gamma rays. However, we show that active interrogation with tagged neutrons is able to provide signatures for the discrimination of uranium against other materials