Fulvio Gini's research while affiliated with Università di Pisa and other places
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Publications (353)
This paper addresses the problem of target detection in a two-channel distributed MIMO passive radar (PR). In this scenario, multiple distributed transmitters emit signals that are received by the two-channel distributed receivers, one channel for surveillance and the other for reference. Both receiver channels are utilized to formulate the target...
Errors in [1] are corrected below. 1. In Eq. (17), $\mathrm{vecs}(\boldsymbol{\Sigma}_{0})$ should be $\mathrm{vec}(\boldsymbol{\Sigma}_{0})$. Specifically, the correct version of Eq. (17) is: \begin{align*} \mathbf{s}_{\boldsymbol{\phi}_{0}}\triangleq\nabla_{\boldsymbol{\phi}}\ln p_{Z}(\mathbf{z};\boldsymbol{\phi}_{0},h_{0})=[\mathbf{s}^{T}_{\bold...
In the design of resource-aware multi-target tracking (MTT) framework for multi-radar systems (MRSs), the estimated target parameters from the previous frame, such as distance, angle, and reflectivity, are generally utilized as prior information to guide resource scheduling at the current frame. However, achieving perfect estimation of these parame...
With the development of miniaturized millimeter wave (MMW) frequency-modulated continuous-wave (FMCW) radar, the dechirp-on-receive technique has been widely used. Due to the limitations of highly integrated radar hardware, it is difficult to further increase the bandwidth of the transmitted signal. Therefore, enhanced range resolution in MMW synth...
In multi-source two-dimensional (2D) direction-of-arrival (DOA) estimation, the essential matching process between the estimated and the true DOAs in the mean square error (MSE) calculation is often based on minimum Euclidean distance criterion, which is substantially different from 1D DOA estimation that is based on simple ordering process. Hence,...
This paper addresses the problem of target detection in a two-channel distributed Multiple-Input Multiple-Output (MIMO) passive radar (PR). In this scenario, multiple distributed transmitters emit signals received by two-channel distributed receivers, with one channel for surveillance and the other for reference. To address this PR detection proble...
Integrated passive radar (IPR) can be regarded as next-generation passive radar technology, which aims to integrate communication and radar systems. Unlike conventional passive radar, which does not prioritize communication-centric radar technology, IPR technology places a higher priority on incorporating specific radar constraints to develop wavef...
Asymptotic analysis is a common tool in statistics aiming at investigating the properties of an inference methodology as the number of observations grows to infinity. Even if the asymptotic regime cannot be achieved in real-world scenarios, its practical usefulness has been proved in an uncountable number of engineering applications. In the contest...
This paper deals with the problem of estimating the parameters of heavy-tailed sea clutter in high-resolution radar, when the clutter is modeled by the correlated Pareto type II distribution. Existing estimators based on the maximum likelihood (ML) approach, integer-order moments (IOM) approach, fractional-order moments (FOM), and log-moments (log-...
In this paper, we address the problem of direction of arrival (DOA) estimation for multiple targets in the presence of sensor failures in a sparse array. Generally, sparse arrays are known with very high-resolution capabilities, where N physical sensors can resolve up to $\mathcal{O}(N^2)$ uncorrelated sources. However, among the many configuration...
This paper concerns direction of arrival (DOA) estimation based on a sparse Bayesian learning (SBL) approach. We address two inherent problems of this class of DOA estimation methods: (i) a predefined dictionary can generate off-grid problems to a SBL DOA estimator; (ii) a parametric prior generally enforces the solution to be sparse, but the exist...
p>Noise can be modeled as a sequence of random variables defined on a probability space that may add to a given dynamical system T that is a map on a phase space. In the nontrivial case of dynamical noise {ε<sub>n</sub>}<sub>n</sub>, where ε<sub>n</sub> ∈ N(0, σ<sup>2</sup>) and the system output is x<sub>n</sub> = T(x<sub>n−1</sub>, x<sub>n−2</sub...
p>Noise can be modeled as a sequence of random variables defined on a probability space that may add to a given dynamical system T that is a map on a phase space. In the nontrivial case of dynamical noise {ε<sub>n</sub>}<sub>n</sub>, where ε<sub>n</sub> ∈ N(0, σ<sup>2</sup>) and the system output is x<sub>n</sub> = T(x<sub>n−1</sub>, x<sub>n−2</sub...
Reinforcement learning (RL) based approaches in massive multiple input multiple output (mMIMO) arrays allow target detection in unknown environments. However, there are two main drawbacks hindering the practical application of these approaches: (i) poor detection performance for weak targets, and (ii) mismatch between high system overhead and singl...
Noise can be modeled as a sequence of random variables defined on a probability space that may be added to a given dynamical system
$T$
, which is a map on a phase space. In the non-trivial case of dynamical noise
$\lbrace \varepsilon _{n}\rbrace _{n}$
, where
$\varepsilon _{n}$
follows a Gaussian distribution
$\mathcal {N}(0,\sigma ^{2})$...
Existing stochastic Ziv-Zakai bound (ZZB) for compressive time delay estimation from compressed measurement relies on a Gaussian approximation, which makes it inaccurate in the asymptotic region when the stochastic component dominates the received signals. In this letter, we apply different random projections on zero-mean Gaussian received signal t...
In the present work, a reinforcement learning (RL) based adaptive algorithm to optimize the transmit beampattern for a co-located massive MIMO radar is presented. Under the massive MIMO regime, a robust Wald-type detector, able to guarantee certain detection performances under a wide range of practical disturbance models, has been recently proposed...
Existing real-valued subspace-based direction of arrival (DOA) estimation methods mainly face two problems: the limitations of uniform linear array (ULA) in practical applications and the presence of virtual mirrored angles. This paper exploits the properties of the virtual signal model of forward/backward average of the array covariance matrix (FB...
It is well-known that the multiple signal classification (MUSIC) algorithm is computationally time-consuming because it requires a complex-valued full-dimension eigenvalue decomposition (EVD) and a complex-valued spectral searching. In this paper, we exploit the virtual signal model of forward/backward average of array covariance matrix (FBACM) to...
This paper investigates the sensitivity to phase synchronization errors through the Hybrid Cramér-Rao Lower Bounds (HCRLB) for joint estimation of target location and velocity in coherent Multiple-Input Multiple-Output (MIMO) radars with distributed antennas. In particular, we derived the HCRLB of range and velocity of a target embedded in Complex...
![FIGURE 5 | CRLBs vs. SCR with different ], Clutter Model I.](publication/359453942/figure/fig4/AS:1139238338854927@1648626994980/CRLBs-vs-SCR-with-different-Clutter-Model-I_Q320.jpg)
![FIGURE 7 | CRLBs vs. ρ, Clutter Model II with ] = 2.1, SCR = 0 dB, and...](publication/359453942/figure/fig5/AS:1139238343053312@1648626995032/CRLBs-vs-r-Clutter-Model-II-with-21-SCR-0-dB-and-v-x-v-y-0-m-s_Q320.jpg)
In this article, we investigate the problem of jointly estimating target location and velocity for widely separated multiple-input multiple-output (MIMO) radar operating in correlated non-Gaussian clutter, modeled by a complex elliptically symmetric (CES) distribution. More specifically, we derive the Cramér–Rao lower bounds (CRLBs) when the target...
This paper deals with the problem of estimating the parameters of heavy-tailed sea-clutter in high-resolution radar, when the clutter is modelled by the correlated Pareto type II distribution. Existing estimators based on the maximum likelihood (ML) approach, integer-order moments (IOM) approach, fractional-order moments (FOM), and log-moments (log...
Beamformers employ an array of antenna elements to collect the electromagnetic wave in spatial domain and filter the corrupted signal in either the element-space or the beam-space. The spatial filtering performance of both element-space and beam-space beamformers is jointly determined by two key factors, beamformer geometry and excitation weights....
In the present work, a reinforcement learning (RL) based adaptive algorithm to optimise the transmit beampattern for a colocated massive MIMO radar is presented. Under the massive MIMO regime, a robust Wald type detector, able to guarantee certain detection performances under a wide range of practical disturbance models, has been recently proposed....
Direction of arrival (DOA) estimation methods suffer from the well-known off-grid problem, that shows up when the true DOAs are not located exactly on the discretized sampling grid points. Existing estimation algorithms should be designed by taking into account the trade-off between density of sampling grids and computational complexity. Moreover,...
Beampattern synthesis of frequency diverse arrays (FDAs) has recently raised increased attention attributed to their range-dependent beampattern. The transmit beampattern of uniform FDA appears
$S$
-shaped, which implies coupling in the range-angle domain and thus causing unwanted energy leakage into the area of non-interest. In this work, we pro...
In this work, we propose a novel strategy of adaptive sparse array beamformer design, referred to as regularized complementary antenna switching (RCAS), to swiftly adapt both array configuration and excitation weights in accordance to the dynamic environment for enhancing interference suppression. In order to achieve an implementable design of arra...
In this work, we propose a novel strategy of adaptive sparse array beamformer design, referred to as regularized complementary antenna switching (RCAS), to swiftly adapt both array configuration and excitation weights in accordance to the dynamic environment for enhancing interference suppression. In order to achieve an implementable design of arra...
This article considers the problem of multitarget detection for massive multiple input multiple output cognitive radar (CR). The concept of CR is based on the perception-action cycle that senses and intelligently adapts to the dynamic environment in order to optimally satisfy a specific mission. However, this usually requires a priori knowledge of...
In the above-named work, [ibid., xxx], there is a typo in the position of the first conjugate operator. The correct definition of the first conjugate operator BN is provided.
This paper concerns the problem of estimating the parameters of the K plus noise distribution. In a previous work, it has been shown that, in the multilook scenario, the modified fractional order moment estimator (MFOME) has about the same estimation accuracy as the [zlog(z)] method, but lower computational complexity. However, significant estimati...
This paper considers the problem of multi-target detection for massive multiple input multiple output (MMIMO) cognitive radar (CR). The concept of CR is based on the perception-action cycle that senses and intelligently adapts to the dynamic environment in order to optimally satisfy a specific mission. However, this usually requires a priori knowle...
Since the seminal paper by Marzetta from 2010, the Massive MIMO paradigm in communication systems has changed from being a theoretical scaled-up version of MIMO, with an infinite number of antennas, to a practical technology. Its key concepts have been adopted in the 5G new radio standard and base stations, where 64 fully-digital transceivers have...
In this paper, we analyze and compare the performance of the CA-CFAR, GO-CFAR and the SO-CFAR detectors in homogeneous and non-homogeneous Weibull background with known shape parameter for Multi-Input Multi-Output radars with widely separated antennas. The non-homogeneity is represented by the presence of interfering targets and a clutter edge in t...
The main aim of this paper is to extend the semiparametric inference methodology, recently investigated for Real Elliptically Symmetric (RES) distributions, to Complex Elliptically Symmetric (CES) distributions. The generalization to the complex field is of fundamental importance in all practical applications that exploit the complex representation...
Since the seminal paper by Marzetta from 2010, the Massive MIMO paradigm in communication systems has changed from being a theoretical scaled-up version of MIMO, with an infinite number of antennas, to a practical technology. Its key concepts have been adopted in the 5G standard and base stations with $64$ fully-digital transceivers have been comme...
This paper studies parameter estimation of a coupled mixture of polynomial phase signal (PPS) and sinusoidal frequency modulated (FM) signal, a newly introduced model motivated by industrial applications. Particularly, we analytically evaluate the estimation performance (or performance loss) via the misspecified Cramer-Rao bound (CRB) when system d...
Focusing on the signal to interference-plus-noise ratio (SINR) maximization in colocated multiple-input multiple-output (MIMO) radars, using the transmit covariance matrix (TCM) design of transmit waveforms, we have proposed a TCM Rpm with the form of symmetrical Toeplitz matrix, where m is the control parameter to generate different TCM. The main...
Existing direction of arrival (DOA) estimation methods in multiple-input multiple-out (MIMO) radar systems will encounter the performance degradation in the cases of few snapshots, low signal-to-noise ratio (SNR), closely spaced targets, or strongly correlated sources. To improve it, this paper develops a new sparse representation-based DOA estimat...
This work focuses on target detection in a colocated MIMO radar system. Instead of exploiting the classical temporal domain, we propose to explore the spatial dimension (i.e., number of antennas $M$) to derive asymptotic results for the detector. Specifically, we assume no a priori knowledge of the statistics of the autoregressive data generating p...
This paper aims at presenting a numerical investigation of the statistical efficiency of the MUSIC (with different covariance matrix estimates) and the IAA-APES Direction of Arrivals (DOAs) estimation algorithms under a general Complex Elliptically Symmetric (CES) distributed measurement model. Specifically, the density generator of the CES-distrib...
The main aim of this paper is to extend the semiparametric inference methodology, recently investigated for Real Elliptically Symmetric (RES) distributions, to Complex Elliptically Symmetric (CES) distributions. The generalization to the complex field is of fundamental importance in all practical applications that exploit the complex representation...
In this paper, we propose a novel algorithm based on fast block LMS (least mean square) adaptive filter, called RD-FBLMS (range-Doppler fast block LMS) for direct path and multipath interferences cancellation in DVB-T (digital video broadcasting—terrestrial) passive bistatic radars (PBRs). These interferences represent some of the major problems in...
This paper has a twofold goal. The first aim is to provide a deeper understanding of the family of the Real Elliptically Symmetric (RES) distributions by investigating their intrinsic semiparametric nature. The second aim is to derive a semiparametric lower bound for the estimation of the parametric component of the model. The RES distributions rep...
A cognitive beamforming algorithm for colocated MIMO radars, based on Reinforcement Learning (RL) framework, is proposed. We analyse an RL-based optimization protocol that allows the MIMO radar, i.e. the \textit{agent}, to iteratively sense the unknown environment, i.e. the radar scene involving an unknown number of targets at unknown angular posit...
This paper proposes an electronic counter countermeasure (ECCM) technique to suppress randomly distributed multiple false targets generated by digital radio frequency memory-based electronic warfare equipment. Firstly, we present the modulation behaviors of deceptive multiple false targets jamming. Afterward, we discuss the ECCM potential of distri...
This letter aims at deriving a Semiparametric Slepian-Bangs (SSB) formula for Complex Elliptically Symmetric (CES) distributed data vectors. The Semiparametric Cram\'{e}r-Rao Bound (SCRB), related to the proposed SSB formula, provides a lower bound on the Mean Square Error (MSE) of \textit{any} robust estimator of a parameter vector parameterizing...
This letter aims at extending the Constrained Semiparametric Cramer-Rao Bound (CSCRB) for the joint estimation of mean vector and scatter matrix of Real Elliptically Symmetric (RES) distributions to Complex Elliptically Symmetric (CES) distributions. A closed form expression for the complex CSCRB (CCSCRB) is derived by exploiting the so-called \tex...
This paper has the twofold goal of providing a deeper understanding of the family of the Real Elliptically Symmetric (RES) distributions by investigating their intrinsic semiparametric nature and, secondly, of deriving a semiparametric lower bound for the estimation of the parametric component of the model. The RES distributions represent a semipar...
This article describes some key ideas and applications of cognitive radars, highlighting the limits and the path forward. Cognitive radars are systems based on the perception-action cycle of cognition that senses the environment, learns relevant information from it about the target and the background, and then adapts the radar sensor to optimally s...
This study focuses on the problem of joint suppression of active jamming in target sector-of-interest (SOI) and out-ofsector interference for colocated compressive sensing multiple-input-multiple-output (CS-MIMO) radar. Three effective strategies for spatial filter measurement matrix (SFMM) design are outlined. Unlike the previous reported Capon be...
This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at the Semiparametric Cram\'{e}r-Rao Bound (SCRB). Semiparametric models are characterized by a finite-dimensional parameter vector of interest and by an infinite-dimensional nuisance function that is often related to an unspecified functional form of...
![Figure 2 -Spectrum opportunities [Gre16].](profile/Pietro-Stinco/publication/323571429/figure/fig2/AS:997215996760067@1614766229503/Spectrum-opportunities-Gre16_Q320.jpg)
This paper describes some key ideas and applications of cognitive radars, highlighting the limits and the path forward. Cognitive radars are systems based on the perception-action cycle of cognition that sense the environment, learn from it relevant information about the target and the background, then adapt the radar sensor to optimally satisfy th...
This chapter aims to provide a comprehensive overview on lower bounds on mean square error (MSE) on the estimation of a deterministic parameter vector under misspecified models. It starts by presenting the theoretical derivation of the so-called misspecified Cramér-Rao bound (MCRB). The asymptotical efficiency of the maximum likelihood (ML) estimat...
Inferring information from a set of acquired data is the main objective of any signal processing (SP) method. In particular, the common problem of estimating the value of a vector of parameters from a set of noisy measurements is at the core of a plethora of scientific and technological advances in the last decades; for example, wireless communicat...
A fundamental assumption underling any Hypothesis Testing (HT) problem is that the available data follow the parametric model assumed to derive the test statistic. Nevertheless, a perfect match between the true and the assumed data models cannot be achieved in many practical applications. In all these cases, it is advisable to use a robust decision...
A fundamental assumption underling any Hypothesis Testing (HT) problem is that the available data follow the parametric model assumed to derive the test statistic. Nevertheless, a perfect match between the true and the assumed data models cannot be achieved in many practical applications. In all these cases, it is advisable to use a robust decision...
This paper deals with a Symbiotic Radar, defined as a Passive Radar that is an integral part of a communication network. The Symbiotic Radar is integrated with an IEEE 802.22 WRAN and linked with the Base Station. It can work as a purely passive radar or, and this is the novelty in the system, can use the Base Station to suggest the best Customer P...
The papers in this special section focus on time/frequency modulated array signal processing. Phased-array is known for its capability to electronically steer a beam towards a desired direction. However, this beam steering does not account for the target range. There is an increasing need to control the range-dependent transmit energy distribution...
This paper considers parameter estimation of a hybrid sinusoidal frequency modulated (FM) and polynomial phase signal (PPS) from a limited number of samples. We first show limitations of an existing method, the high-order ambiguity function (HAF), and then propose a new method by adopting the high-order phase function which was originally designed...
This paper focuses on some applications of cognitive radars. Cognitive radars are systems based on a perceptionaction cycle that sense the environment and learn from it important information on the target and the background, then adapt the transmitted waveform to optimally satisfy the needs of their mission according to a desired goal. Both active...
Scatter matrix estimation and hypothesis testing are fundamental inference problems in a wide variety of signal processing applications. In this paper, we investigate and compare the matched, mismatched, and robust approaches to solve these problems in the context of the Complex Elliptically Symmetric (CES) distributions. The matched approach is wh...
Different from conventional phased-array radars, the frequency diverse array (FDA) radar offers a rangedependent beampattern capability that is attractive in various applications. The spatial and range resolutions of an FDA radar are fundamentally limited by the array geometry and the frequency offset. In this paper, we overcome this limitation by...
Recently, cyclostationarity (CS) based detection methods exploiting the autocorrelation periodicity property of the orthogonal frequency division multiplexing (OFDM) signals attracted a lot of attention. These detection methods are more complex than energy detection but they have better detection performance in low-SNR regimes. The drawback, howeve...
Citations
... Problem (10) is a non-convex NP-hard problem due to the CMC (|x| = 1) and main lobe constraint (x H Mx ≥ E 0 ). While the CMC has been well tackled in the literature [54]- [56] by iterative algorithms, the main lobe constraint has not been considered yet. There are two main challenges with the main lobe constraint: Firstly, it is a non-convex constraint that needs an accurate convex relaxation. ...
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... Furthermore, Nguyen and Lee [8] modified the computational network using the combination of network inputs. Another example of utilizing deep learning in telecommunications is the research conducted by Pavel et al. [9]. In their work, they employ a deep neural network to acquire knowledge about the optimal compressive sampling matrix. ...
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... Reinforcement Learning (RL), known for its adaptability to dynamics without prior assumptions, has garnered attention in applications to ISAC systems in [12,13]. However, applying RL to the considered doubly-dynamic problem still faces two main difficulties: Firstly, existing RL algorithms struggle to handle complex constraints in this problem. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/534489136472065-1504443548078_Q64/Xiangrong-Wang.jpg)
... Following that, many DOA estimation algorithms based on sparse algorithms have been proposed, such as matching pursuit (MP) [18], orchogonal matching pursuit (OMP) [19], etc. The initial sparse decomposition method is limited by the density size of the grid, and to solve this limitation, many sparse decomposition methods on off-grid have been proposed [20] [21] [22]. However, this class of algorithms still suffers from practical problems such as large computational effort. ...
... At the outset, video anomaly detection relied on traditional, handcrafted feature-based methods [8,9], which were inefficient and time-consuming. However, with the development of deep learning theories and methods in frame processing, such as object recognition [10,11], object detection [12,13], and behavior prediction [14], many modern deep neural network-based approaches have gradually been applied to video anomaly detection. ...
... For any perturbed orbit of the system x(ε) = (x 0 , T (x 0 ) + ε 1 , T (T (x 0 ) + ε 1 ) + ε 2 , . . . ), it holds [28]: ...
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... However, some researches have shown that the adjacent reflectivity in extreme weather targets varies dramatically and the gradient often ranges from 30 to 40 dBZ within 1 km, sometimes even reaching 55 dBZ/km [12][13][14]. In order to realize the detection of weather targets with high gradient-reflectivity phenomenon, a very effective sidelobe suppression strategy must be adopted to avoid the artifact caused by range sidelobes [15], while the sidelobe performances of NLFM waveform are not enough to meet the accuracy of the quantitative detection of distributed scatterers, and the sidelobe needs to be further suppressed. ...
... The traditional SSL method is based on the signal/channel model and signal processing and has made significant progress over the years. Currently, mainstream SSL methods include beamforming [3], time delay of arrival [4], and high-resolution spectrum estimation [5]. All of these methods achieved good localization performance in free space. ...
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... Ψ (m, n) = In terms of classical theory, the CFAR method is often combined with a variety of distribution models (k distribution, Weibull distribution, normal distribution, GP distribution) and applied in the underwater acoustic signal beamforming and target automatic detection [106,107]. Shen designed a special CFAR detector using the reverberation properties of the ocean [108,109]. It could analyze the active sonar echo and fit the data efficiently. ...
... 图 18 加入特征金字塔后的AD-CNN算法 [50] Fig. 18 AD-CNN algorithm after adding feature pyramid [50] Fig. 19 Flow diagram of the multi-channel characterization module [54] 12 (a) 不同层特征图对应的热力图 (a) Thermal maps corresponding to different layer characterization maps (b) 热力图叠加到原图结果 (b) Heat map superimposed on original map results 图 21 NAS-FPN热力图结果 [58] Fig. 21 NAS-FPN heat map results [58] Fig. 27 Overall framework of SAR target detection method combined with reinforcement learning [70] ...
