Target DoA estimation in passive radar using non-uniform linear arrays and multiple frequency channels

In this paper we present a robust approach for target direction of arrival (DoA) estimation in passive radar that jointly exploits spatial and frequency diversity. Specifically we refer to a DVB-T based passive radar receiver equipped with a linear array of few antenna elements non-uniformly spaced in the horizontal dimension, able to collect multiple DVB-T channels simultaneously. We resort to a maximum likelihood (ML) approach to jointly exploit the target echoes collected across the antenna elements at multiple carrier frequencies. Along with an expected improvement in terms of DoA estimation accuracy, we show that the available spatial and frequency diversity can be fruitfully exploited to extend the unambiguous angular sector useful for DoA estimation, which represent an invaluable tool in many applications. To this purpose, a performance analysis is reported against experimental data collected by a multi-channel DVB-T based passive radar developed by Leonardo S.p.A

Auto-regressive model based polarimetric adaptive detection scheme part II: Performance assessment under spectral model mismatch

This work addresses the problem of target detection in coherent radar systems equipped with multiple polarimetric channels. In “Part I” of this two-part study, a multi-channel auto-regressive model based polarimetric detection scheme has been developed and its performance has been studied against clutter with characteristics exactly matching the adopted parametric model. In this second part of the study, the performance assessment is extended, by means of theoretical and simulated analyses, to include the case of disturbance components with diverse spectral characteristics. Consequently, an appropriate modification is introduced to the detection scheme to make it robust to typical spectral mismatches occurring in practical situations. Finally, the effectiveness of the resulting detection scheme is proved against simulated and experimental data

A practical approach to polarimetric adaptive target detection in passive radar

Recently, the exploitation of polarimetric diversity was considered as a way to improve target detection capability in passive radar systems. Specifically, it was shown that a locally adaptive Polarimetric - Generalized Likelihood Radio Test (PGLRT) detection scheme might represent an effective solution for passive radar exploiting different signals of opportunity. However, depending on the considered application, it could be highly computationally expensive. The present work presents an alternative lower-cost approach, based on a global adaptation of the polarimetric whitening filter. The proposed scheme is tested against experimental data collected by means of a dual-pol receiving system. The reported analysis shows that it allows comparable performance with respect to the previously introduced approach, especially when operating against scenarios characterized by strong interfering sources

Auto-regressive model based polarimetric adaptive detection scheme part I: Theoretical derivation and performance analysis

This paper deals with the problem of target detection in coherent radar systems exploiting polarimetric diversity. We resort to a parametric approach and we model the disturbance affecting the data as a multi-channel autoregressive (AR) process. Following this model, a new polarimetric adaptive detector is derived, which aims at improving the target detection capability while relaxing the requirements on the training data size and the computational burden with respect to existing solutions. A complete theoretical characterization of the asymptotic performance of the derived detector is provided, using two different target fluctuation models. The effectiveness of the proposed approach is shown against simulated data, in comparison with alternative existing solutions

Polarimetric passive radar. A practical approach to parametric adaptive detection

Polarimetric diversity has been recently shown to significantly improve the target detection performance in passive radar systems, if properly exploited to mitigate the competing interference. An adaptive processing scheme is presented in this work, leveraging the information conveyed using multi-polarized receiving antennas and modeling the disturbance as a multichannel autoregressive process. Despite this approach operates with a limited number of adaptive degrees of freedom, the long integration time exploited by passive radar typically requires a substantial computational cost and ad hoc expedients for its application. Therefore, a modified cost-effective implementation of the conceived solution is proposed in order to reduce the computational burden while controlling the resulting loss. The authors extensively demonstrate the effectiveness of the proposed solution against experimental data collected by a FM radio based passive coherent location system. The experimental results show that the proposed processing scheme yields a remarkable improvement with respect to both the conventional processing at the single polarimetric channel and the state-of-the-art strategies exploiting polarization diversity in PCL systems

Computationally effective range migration compensation in PCL systems for maritime surveillance

In this paper, we consider the possibility of extending the coherent processing interval (CPI) as a way to improve target detection capability in passive radars for maritime surveillance applications. Despite the low velocity of the considered targets, range walk effects could limit the performance of the system when long CPIs are considered. To overcome these limitations while keeping the computational load controlled, we resort to a sub-optimal implementation of the Keystone Transform (KT), based on Lagrange polynomial interpolation, recently presented by the authors and successfully applied against aerial targets. Following those promising results, we extend the proposed approach to a coastal surveillance scenario. In the considered case, since longer CPI values are used, the proposed strategy appears to be even more attractive with respect to a conventional KT implementation based on the Chirp-Z Transform interpolation. In fact, comparable detection performance are obtained with a remarkable computational load saving. In detail, the effectiveness of the proposed approach is demonstrated against experimental data provided by Leonardo S.p.A., using a DVB-T based passive radar

Functional connectivity changes and their relationship with clinical disability and white matter integrity in patients with relapsing-remitting multiple sclerosis

Background and objective: To define the pathological substrate underlying disability in multiple sclerosis by evaluating the relationship of resting-state functional connectivity with microstructural brain damage, as assessed by diffusion tensor maging, and clinical impairments. Methods: Thirty relapsing–remitting patients and 24 controls underwent 3T-MRI; motor abilities were evaluated by using measures of walking speed, hand dexterity and balance capability, while information processing speed was evaluated by a paced auditory serial addiction task. Independent component analysis and tract-based spatial statistics were applied to RS-fMRI and diffusion tensor imaging data using FSL software. Group differences, after dual regression, and clinical correlations were modelled with GeneralLinear-Model and corrected for multiple comparisons. Results: Patients showed decreased functional connectivity in 5 of 11 resting-state-networks (cerebellar, executive-control, medial-visual, basal ganglia and sensorimotor), changes in inter-network correlations and widespread white matter microstructural damage. In multiple sclerosis, corpus callosum microstructural damage positively correlated with functional connectivity in cerebellar and auditory networks. Moreover, functional connectivity within the medial-visual network inversely correlated with information processing speed. White matter widespread microstructural damage inversely correlated with both the paced auditory serial addiction task and hand dexterity. Conclusions: Despite the within-network functional connectivity decrease and the widespread microstructural damage, the inter-network functional connectivity changes suggest a global brain functional rearrangement in multiple sclerosis. The correlation between functional connectivity alterations and callosal damage uncovers a link between functional and structural connectivity. Finally, functional connectivity abnormalities affect information processing speed rather than motor abilities

A flexible design strategy for three-element non-uniform linear arrays

This paper illustrates a flexible design strategy for a three-element non-uniform linear array (NULA) aimed at estimating the direction of arrival (DoA) of a source of interest. Thanks to the spatial diversity resulting from non-uniform sensor spacings, satisfactory DoA estimation accuracies can be achieved by employing a very limited number of receiving elements. This makes NULA configurations particularly attractive for low-cost passive location applications. To estimate the DoA of the source of interest, we resort to the maximum likelihood estimator, and the proposed design strategy is obtained by constraining the maximum pairwise error probability to control the errors occurring due to outliers. In fact, it is well known that the accuracy of the maximum likelihood estimator is often degraded by outliers, especially when the signal-to-noise power ratio does not belong to the so-called asymptotic region. The imposed constraint allows for the defining of an admissible region in which the array should be selected. This region can be further modified to incorporate practical design constraints concerning the antenna element size and the positioning accuracy. The best admissible array is then compared to the one obtained with a conventional NULA design approach, where only antenna spacings multiple of λ/2 are considered, showing improved performance, which is also confirmed by the experimental results

Click-connected 2-(hydroxyimino)aldehydes for the design of UV-responsive functional molecules

Click chemistry is used to functionalize simple lipophilic and water-soluble molecules, a complex PEGylated phospholipid (DSPE-PEG2000), and two benzylic substrates with the 2-(hydroxyimino)aldehyde (HIA) group. To this end, two terminal alkynes bearing the HIA moiety were synthesized and coupled to different azides through copper(I)-catalyzed azide alkyne cycloaddition (CuAAC). Norrish–Yang photoisomerization (λ= 365 nm, LED source) is successfully obtained, with no interference by the triazole linker, except when the forbidden n-π* carbonyl transition is screened by a remote substituent such as salicylaldehyde. UV-Vis spectrometry suggests a specific interaction of HIAs with Cu(II), whereas no such evidence is found with Cu(I). We thereby show that the CuAAC methodology can be used successfully to obtain HIA-based UV-responsive hydrophilic or lipophilic ligands, phospholipidic components for the construction of liposomes, and macrocycle precursors. © 2020 Wiley-VCH Gmb

Reference-free amplitude-based WiFi passive sensing

The parasitic exploitation of WiFi signals for passive sensing purposes is a topic that is attracting considerable interest in the scientific community. In an attempt at meeting the requirements for sensor compactness, easy deployment, and low cost, we resort to a non-coherent signal processing scheme that does not rely on the availability of a reference signal and relaxes the constraints on the sensor hardware implementation. Specifically, with the proposed strategy, the presence of a moving target echo is determined by detecting the amplitude modulation that it produces on the direct signal transmitted from the WiFi access point. We investigate the target discrimination capability of the resulting sensor against the competing interference background and we theoretically characterize the impact of undesired amplitude fluctuations in the received signal that are determined by causes other than the superposition of the target echo, thereby including the waveform properties. Hence, we propose different solutions to address the limitations identified, characterized by different complexities, and we investigate their advantages and drawbacks. The conceived signal processing schemes are thoroughly validated on both simulated and experimental data, collected in different operational scenarios