Search

In this article, a commercial low cost solution for increasing DVB-T based passive radar (also referred to as passive coherent location) robustness with respect to channel allocation and range resolution, is designed. IDEPAR demonstrator is updated to include a new recording system in charge of DVB-T channels reallocation. The use of commercial hardware introduces frequency mismatching between acquired channels that compromises system operation. To face channel frequency alignment, fulfilling the requirements imposed by the high Doppler resolution typical of passive radars, a novel compensation algorithm is proposed, based on the minimization of signal dispersion in the Cross-Ambiguity Function domain. The well-known cyclic prefix van de Beek method is used as reference. Results show an increase in target signal to interference ratio and detection performances, as well as a reduction of clutter dispersion when the novel proposed algorithm is applied. The low cost solution is also compared to a high performance one capable of acquiring a wide bandwidth of sparse DVB-T channels, and performing channel reallocation by digital signal processing. Results show that both systems reached similar performances in terms of range resolution and SNR improvement. more...

Global Positioning System (GPS) satellites are promising illumination opportunity for Passive Radar systems due to their global coverage and the availability of multiple satellites wherever over the world, but their low power at ground level limits system coverage. In this paper, a GPS based Passive Radar exploiting digital array processing techniques is presented for ground target location. To face signal level problems, a processing scheme combining reconstructed reference signals, adaptive filtering techniques and spatial filtering is implemented. Conventional beamforming techniques are used to increase target echo level before the detection stage, and high resolution DoA estimation techniques are applied to estimate targets' azimuth. Tacking into account the system geometry, range and azimuth information, ground targets can be located. Real radar data is used to analyse system operation. During the measurement campaign, a cooperative vehicle was employed for validation purposes. Results confirm GPS signals for ground targets detection and localization. more...

A reflectarray antenna with an optimized sectorial beam is designed for the surveillance channel of a DVB-S-based passive radar (PR). The employment of satellite illuminators requires a high gain antenna to counteract the losses due to the great distance from the transmitter, but without forgetting a beamwidth wide enough to provide angular coverage. A method based on optimizing the position of several contiguous beams is proposed to achieve the required sectorial pattern. Different reflectarray elements are designed to achieve S-curves with smooth slopes and covering all the required phases (the S-curve represents the reflection phase of a single element, as a function of size, rotation and incidence angle). The real phase and modulus of the reflection coefficient of each element are considered in the optimization process to achieve the best real prototype. Geometry has been studied and adapted to employ commercial elements for the feed, feed-arm and the structure that holds the aperture. The designed prototype has been characterized in an anechoic chamber achieving a stable gain greater than 19 dBi in almost the complete DVB-S band, from 10.5 GHz to 12 GHz with a sectorial beam of 8.7∘×5.2∘. The prototype has also been validated in PR trials in terrestrial scenarios allowing the detection of cars at distances up to 600 m away from the PR, improving the performance achieved with commercial parabolic dish antennas. more...

An upgraded version of IDEPAR demonstrator capable of detecting and extracting parameters from targets in a 4D measurements space(range, Doppler, azimuth and elevation) is presented to allow the localization of small aerial drones in the Cartesian space (x,y,z). A two-stage spatial filtering processing scheme based on a 2D reception antenna system provides target's directions of arrival (azimuth, elevation) for targets' localization in the Cartesian space. The PR system was validated in measurement campaigns using small drones confirming the location capabilities of the proposed approach. more...

$A$ 3D (range, Doppler, Azimuth) detection approach based on spatial non-coherent integration is proposed for improving DVB-T based Passive Radar (PR) detection capabilities. Integration is performed in a transformed beam space generated by digital array signal processing, and incoherent integration along the azimuth dimension. To consider the correlation of integrated reference cells, a CFAR technique is designed based on threshold modelling using Monte-Carlo simulations, that provides 3D plots. System performance is compared to that obtained with a scheme performing 2D CFAR detection in range-Doppler, and DoA estimation in separate processing stages. Results obtained in measuring campaigns designed for studying the suitability of DVB-T PRs for drone detection, prove a significant detection improvement with respect to the considered reference scheme. more...

Passive Radars (PRs) are promising emerging technologies to face new security requirements. Satellite illuminators are of great interest due to their nearby global coverage and availability, operating frequencies and waveforms. The main challenges are related to high transmission losses, which limit the coverage areas. A study of DVB-S capabilities as IoO is presented and first results of ground targets detection in a semi-urban scenario are presented. The employment of commercial parabolic antennas for acquiring both the reference and surveillance channel limits the angular coverage and therefore, the scenario of the PR. Results confirmed the feasibility of DVB-S PRs for low range ground target detection and tracking, and pointed out the effects of target echoes Doppler spreading along the signal processing chain, whose analysis is a key step towards the proposal of solutions to increase detection performance. more...

International audience; Main advantages of employing DVB-S as Illumina-tor of Opportunity for passive radar is high availability, but the power scattered from targets is really low. In this paper, the design of a surveillance antenna capable of fulfilling the requirements defined by the DVB-S passive radar, is carried out. Detection and tracking capabilities of ground targets are considered. A high gain antenna is required for fulfilling range coverage requirements, together with an azimuth beamwidth that provides the required angular one.To tackle this challenge, a sectorial beam reflectarray antenna is selected. For designing it, a method based on optimizing the steering of a set of beams that form of the sectorial pattern is proposed. The losses from reflectarray cells are introduced, optimizing the distribution of elements by selecting the best phase for the central one. The reflectarray is designed studying the geometric and feeding parameters and it is simulated in ANSYS HFSS achieving a sectorial beam of 7.4° (azimuth) x 2.3° (elevation) with a realized gain of 28.38 dBi. more...

In this paper, the impact of the drone airscrews signature in passive radars exploiting Digital Video Broadcasting signals is tackled. Beamforming techniques optimized to minimize the variance of the interference using the statistical characterization of real clutter data followed by a CFAR detector are used to detect drones and their associated airscrews signature. An independent bi-dimensional tracker based on the Kalman filter is proposed to tackle the drone and airscrews tracking process, and to extract micro-Doppler signature features. Real radar data acquired by a technological demonstrator developed at the University of Alcala were used to evaluate the proposed solution. Results proved the suitability of the proposed detection and tracking schemes for airscrews signature feature extraction. Ansys HFSS electromagnetic simulator validated the results. more...

Ultra high frequency (UHF) passive ground clutter statistical models were determined from real data acquired by a passive radar for the design of approximations to the Neyman–Pearson detector based on machine learning techniques. The cross-ambiguity function was the input space without any preprocessing. The Gaussian model was proved to be suitable for high Doppler values. Other models were proposed for Doppler close to zero, where ground clutter and low bistatic Doppler targets concentrate. Likelihood ratio detectors were built for this Doppler region, and a neural-network-based adaptive threshold technique was designed for fulfilling false alarm requirements throughout all the input space. The proposed scheme outperformed a conventional passive radar one and could be used as a reference for future designs. more...

Artificial intelligence techniques were applied for detecting small moving targets in maritime clutter environments. Neural detectors are considered to approximate the Neyman–Pearson (NP) in composite hypothesis testing problems. Sub-optimum approaches based on the Constrained Generalized Likelihood Ratio (CGLR) were analysed, and compared to conventional implementations based on Doppler filtering that are designed to filter clutter and improve the Signal-to-Interference Ratio, and Constant False Alarm Rate techniques. The CGLR performance was significantly better at the expense of a high computational cost. As a solution, neural network training sets were designed for approximating the NP detector. The detection of small boats in Gaussian clutter was the defined case study in order to assume the design hypothesis of the conventional solutions and to study their performance under their most favourable conditions. Detection schemes were evaluated using real radar data. Neural solutions based on Second Order Neural Networks provide the best results, being able to approximate the CGLR with a significantly low computational cost compatible with real-time operations. more...

A study of the potentials of Global Positioning System (GPS) satellites as passive radar illuminators for ground target detection is presented. GPS signals are promising due to their global coverage and the availability of multiple satellites wherever over the world. The main drawback is the low power at ground level that limits system coverage. For coherent processing, the Cross Ambiguity Function (CAF) is generated using reconstructed reference signals. Signal to noise ratio can be increased by coherent integration in the CAF domain. This approach has been studied for commercial air-planes and ships of different sizes (from ferries to fishing boats). In this paper, the detection of cars in a semi-urban environment is considered. The demonstrator IDEPAR was updated for GPS reception using commercial hemispherical GPS antennas. During the measurement campaign, a cooperative target was employed for validation purposes. Results confirmed the system capabilities for ground target detection in low range conditions. These first results are a probe of concept and motivate the design of directive GPS surveillance antennas and multistatic processing for improving the achievable coverages. more...

This paper tackles the oil spills offshore monitoring using satellite Earth Observation tools based on Synthetic Aperture Radar (SAR) sensors. The proposed processing scheme is based on modelling SAR sea backscattering assuming a Generalized Gamma Distribution clutter. The signal processing scheme includes a first stage to define the non-homogeneous area due to the presence of dark spots in function of the multi-scale estimations of a textural parameter defined as the inverse of the product between shape and scale sea clutter parameters. After an statistical study of this parameter, a robust value can be defined for comparison purposes. In the resulted search area, an adaptive thresholding is performed to obtain a segmented image with the oil slicks candidates contouring at pixel level. Results obtained with SAR images acquired by Sentinel-1 over Corsica, confirm the suitability of the proposed methodology. more...

This paper tackles the monitoring of oil spills using satellite Earth Observation tools based on Synthetic Aperture Radar (SAR) sensors. The proposed processing scheme is composed by a dark spot detector and the discrimination of false positives using, in both stages, instantaneous wind field information. The detector implements an adaptive threshold to provide robust performance against speckle noise and wind conditions. Focusing on the typical evolution of elongated slicks, a classification is performed. Results obtained with a SAR image acquired by TerraSAR-X over the Gulf of Mexico and the co-registration with weather forecasts, confirm the suitability of the proposed methodology. more...

Main advantages of employing DVB-S as Illuminator of Opportunity for passive radar are high availability and possibility of radar imaging. In this article, detection, tracking and radar imaging of ground targets are considered, focussing in the design of surveillance antennas capable of fulfilling the requirements defined by the DVB-S passive radar. High gain antenna is required due to low scattered power from the targets but, simultaneously, a wide azimuth beamwidth is mandatory to generate interesting cross-range resolutions from Inverse Synthetic Aperture Radar images relying on the target translation motion. To tackle this challenge, a dual-feed reflectarray generating two simultaneous overlapping beams, with a common phase center and different pointing directions, is proposed. This solution, by means of the sum-pattern of both beams, improves detection, tracking and radar imaging performances. As an added value, it allows the implementation of monopulse techniques. more...

In this paper, the design of a broadband modified-circle-shape patch antenna with H-aperture feeding is presented, to be used as single radiating element in the array of the surveillance channel of an UHF passive radar. Different techniques are proposed to achieve a relative bandwidth of more than 30%, and challenging radiation pattern characteristics for the defined application. The achievement of these requirements is proved through measurements in anechoic chamber. A NULA is designed using optimization techniques and considering coupling effects between elements. The NULA was integrated in IDEPAR, the passive radar demonstrator developed in the University of Alcala, and validated through measurement campaigns. Results prove a significant improvement of the passive radar target detection and bearing estimation capabilities. more...

This work tackles terrestrial targets monitoring using a Passive Radar System (PRS) characterized by a surveillance channel processing composed of a Neyman-Pearson (NP) detector and three-dimensional tracker implementation. The NP detector is a parametric approach that requires the prior knowledge of target and bistatic clutter statistical models at communication systems frequencies that fit with real data. The proposed tracker provides three-dimensional (range, azimuth and speed) trajectories declaration exploiting the capabilities of beamforming techniques based on a uniform linear array as surveillance antenna system. The considered solution is validated with real data acquired by a PRS in a semi-urban scenario. more...

This paper tackles the oil spill look-alikes detection based on multi-resolution technique using Synthetic Aperture Radar (SAR) images acquired in X band. SAR sensors are powerful tools for Earth Observation but automatic interpretation is very difficult. As oil spills appear as dark spots, the first processing stage is the look-alikes detection. A segmentation based on texture parameters, to define the potential areas with dark spots, and sea clutter statistics, to determine an adaptive threshold, is proposed. The dark spot detection scheme is evaluated with real X-Band SAR data, and detection performances allow to improve the accuracy in later feature extraction tasks. more...

The problem of electromagnetic characterization of composite materials used for the airframe of aircrafts is considered. A measurement methodology is proposed for estimating the associated conductivity. This parameter is critical for the definition of antenna emplacement on the airframe keeping in mind the impact of the presence of the platform and other antenna systems on its performance. This is specially important in small size aircraft, as UAVs. Presented preliminary results are really promising. Specimens of PCN (Polymer-Clay Nanocomposite) material are used, which include metallic meshes for improving material performance against lightning. more...

Drones are considered an important threat for critical infrastructures, and for people in crowded environments, because they can carry explosives, chemicals, or biological agents, cameras, etc. Passive radars are emerging sensor technologies that use non-cooperative illuminators instead of a dedicated transmitter. This feature makes them attractive candidates due to the absence of transmitted power. In this work, the viability of passive radars for detecting drone-like targets has been studied. Theoretical coverage studies based on bistatic radar cross section simulations and complex propagation models predict the possibility of drone detection with passive radars. Theoretical results have been validated with real experiments using the IDEPAR demonstrator, developed at the University of Alcala. more...

One of the advantages associated to the use of passive radars is the lower development and maintenance costs with respect to active ones, mainly related to the absence of a dedicated transmitter and to the possibility of using COTS components. In this paper, a study of the advantages of using Non Uniform Linear Arrays (NULAs) for the design of the antenna system for a passive radar exploiting DVB-T signals is carried out, considering as a basic requirement the use of commercial antennas. Commercial solutions are not designed for being used as single radiating elements in array configurations, so directivity and physical sizes are not the most desirable for array design. In Spain, the use of horizontal polarization includes additional constraints to inter-element distances, and usually gives rise to grating lobes. NULAs designed using optimization techniques for maximizing directivity and controlling side lobes levels are analyzed and compared to Uniform Linear ones (ULAs), proving the better performance of the NULA based spatial filtering. For a selected commercial antenna, performances of NULAs and ULAs are compared as a function of the number of elements, showing a better improvement as the number of elements increases. For completing the study, the single radiating element is redesigned for reducing the physical size maintaining the radiation properties, although the cost associated to this new design is clearly higher than the first one. Results show that NULAs with smaller elements give a better performance in terms of Side Lobe Level (SLL). more...

Bistatic radar clutter can be characterized considering the Cross-Ambiguity Function (CAF) output as the observation space, for formulating the optimum Neyman-Pearson detector. In a previous study, a bank of Likelihood Ratio (LR) detectors was designed, but a basic passive radar solution composed of an incoherent Constant False Alarm Rate applied to the CAF intensity was used as reference. In this paper, the study is completed considering a widespread solution based on an Extensive CAncellation filter before CAF generation. Performances are estimated using real data acquired in a semi-urban scenario for the detection of ground targets. Estimated probabilities of detection and false alarm confirm the superior performance of the bank of LR filters compared to the basic and the new reference solutions. more...

Passive radars exploit the signal transmitted by other systems, known as opportunity illuminators (OIs), instead of using their own transmitter. Due to its almost total invulnerability to natural disasters or physical attacks, satellite OIs are of special interest. In this line, a feasibility study of Earth Observation Synthetic Aperture Radar (EO SAR) systems as OIs is carried out taking into consideration signal waveform, availability, bistatic geometry, instrumented coverage area and incident power density. A case study based on the use of PAZ, the first Spanish EO SAR, is presented. PAZ transmitted waveform, operation modes, orbit characteristics and antenna and transmitter parameters are analyzed to estimate potential coverages and resolutions. The study concludes that, due to its working in on-demand operating mode, passive radars based on PAZ-type illuminators can be proposed as complementing tools during the sensor commissioning phase, for system maintenance and for improving its performance by providing additional information about the area of interest and/or increasing the data updating speed, exploiting other sensors during the time PAZ is not available. more...

Neural Networks based CFAR techniques are proposed in an improved coherent radar detector.A coherent detector using a unique CFAR is compared to the classical bank of CFAR techniques.The filter bank output is statistically analyzed to prove Gaussian CFARs unfeasibility.The proposed neural CFAR can be applied to any clutter distribution or detection strategy.A comparative study is carried out on a simulated scenario with complex target trajectories. This paper tackles the detection of radar targets with unknown Doppler shift in presence of clutter. A Neural Network based Constant False Alarm Rate (CFAR) technique is proposed for adapting the detection threshold in an improved architecture based on the Generalized Likelihood Ratio (GLR) detector. Detection schemes based on Doppler processors (Moving Target Indicator (MTI) and Moving Target Detector (MTD)) and conventional CFAR detectors are considered as reference. In these reference solutions, interference is assumed Gaussian and white at the output of each Doppler filter, so conventional incoherent CFAR detectors are applied. The outputs of the CFAR detectors are combined using an OR operation to decide the presence of a target if, at least, one of the CFARs declares it. As a result, the P FA is higher than the desired one, as we prove. In this paper, an improved detector is presented that combines the following features: a better approximation to the Neyman-Pearson detector based on the GLR (selecting the maximum filter bank output), and a unique CFAR detector applied to the squared modulus of the maximum filter bank output. Due to the non-linear nature of the maximum function, conventional CFAR detectors are not suitable. A Neural Network CFAR solution is proposed. A general design method is presented. Results prove that the designed CFAR allows the exploitation of the better detection capabilities of the detector based on the maximum function, providing a higher probability of detection while fulfilling the probability of false alarm requirement. The proposed method can be extended to other detection strategies and radar scenarios. more...

This paper tackles the study of the sensitivity of the characteristics and detection capabilities of a passive radar based on DVB-T signals with respect to channel availability. Real data acquired by IDEPAR demonstrator (developed by the University of Alcala) were considered. The ambiguity function of one, two and three consecutive channels is calculated to estimate the pedestal mean level and the spike width. A reduction of the detection performance is obtained due to an increase of the pedestal mean level and a degradation of the range resolution associated with a lower information bandwidth. The detection probability provided by IDEPAR confirms the dependence on the spectrum. This sensitivity should be taken into account to design a passive radar that fulfils detection requirements. more...

This paper presents a study about the possibility of using Passive Radar ISAR imaging for target classification. Some features are proposed which allow to separate target classes using simple classifiers. Due to the lack of big databases for training and testing, the study is focused on the pre-processing chain to calculate useful features related to the target properties, that are useful for target classification. Features are useful if the values for different classes are separable in the features space. The possibility of designing target classifiers is demonstrated for the first time with Passive Radar ISAR imagery. more...

The design process of the single radiating element for a digital terrestrial television based passive radar antenna array is presented. Design requirements were analyzed considering the specific application, and patch antenna technology was finally selected. The complete design process is presented for a single element operating at 700 MHz with a fractional bandwidth close to 19%. The final solution is a E shaped patch, using air gap as substrate and coaxial feeding. Antenna performance parameters were simulated using ANSYS HFSS. A prototype was built and characterized in an anechoic chamber. Measurements proved the correct performance of the antenna for a passive bistatic radar system. more...

This paper tackles the study of the nondesired effects in the detection capabilities and system resolution of Passive Radar (PR) solutions due to sporadic interference. Real radar data acquired by IDEPAR demonstrator (DVB-T based PR system developed by the University of Alcala) with the presence of an interference were considered. The ambiguity function is calculated to estimate the pedestal mean level and the equivalent information bandwidth. A degradation of the range resolution and a reduction of the Signal-to-Noise Ratio are observed. A simulated radar scenario was designed using the acquired data and adding terrestrial targets to obtain a good approximation of a real environment. Although the resulted detection capabilities are reduced, the target trajectories can be identified. This trend can be explained based on the power migration along range dimension associated with the interference bandwidth, generating blind Doppler shifts in the detection stage. Then, these nondesired effects should be taking into account to improve the PR availability against sporadic interferences. more...

Passive Radar systems (PR) are an emerging technology that due to its special characteristics must be considered for being used for detection, management and surveillance applications with low environmental impact, making them attractive for the smart city concept. A study of space-borne illuminators for passive radar systems in terrestrial traffic monitoring applications is presented, focusing on the GPS satellite constellation. The study includes the estimation of the bistatic radar cross section of a commercial car model that provides challenging low values that make detection tasks more difficult. The effects on the system geometry the relative movement of the satellite platforms gives rise, are also analyzed. more...

In this paper, a patch antenna designed to operate in a UHF passive radar with a broadband about 19% is validated in a real semi-urban scenario. Novel techniques, such as using air gap as substrate and E shaped patch, were considered in the fabrication. The proposed solution is used in the surveillance acquisition system of IDEPAR demonstrator, a DVB-T based passive radar system, to evaluate the detection performance with real radar data acquired in a terrestrial scenario. more...

Coherent CFAR (Constant False Alarm Rate) detectors were designed and evaluated in non-homogeneous DVB-T (Digital Video Broadcasting-Terrestrial) passive radar scenarios. Conventional CFAR techniques are usually applied to noncoherent detector that can not be optimal attending to Neyman-Pearson criterion. The capability to approximate function of neural networks (NN) was used to maintain the false alarm rate without a priori knowledge of the optimum detector outputs. In addition, variability index (VI) was used to provide robustness against non-homogeneous interference. The considered detection scheme was evaluated with real passive radar data acquired by IDEPAR demonstrator, a DVB-T passive radar system, in a terrestrial scenario. Results confirm the potentiality of the coherent VI-MLP-CFAR detector as a low-cost solution for traffic monitoring. more...

A non-uniform linear array architecture was selected for the design of the surveillance channel antenna of a passive bistatic radar exploiting Digital Video Broadcasting-Terrestrial signals. The use of commercial radiating elements and the possibility of implementing beamforming techniques for the generation of simultaneous beams were the main requirements. A commercial antenna was characterized by electromagnetic simulations and uniform and non-uniform linear arrays were designed. Optimization techniques based on a genetic algorithm were applied for guaranteeing the beam steering throughout 60° (the single element azimuth beam-width), with a maximum side lobe level of 12dB at the limit steering angles. more...

This work tackles terrestrial traffic monitoring using a Passive Radar System (PRS) characterized by a surveillance channel processing composed of a Neyman-Pearson (NP) coherent detector and three-dimensional tracker implementation. The NP detector is a parametric approach that requires the prior knowledge of target and bistatic clutter statistical models at communication systems frequencies that fit with real data. The proposed tracker provides three-dimensional (range, azimuth and speed) trajectories declaration exploiting the capabilities of beamforming techniques based on a uniform linear array as surveillance antenna system. The considered solution is validated with real data acquired by a PRS in a semi-urban scenario. more...

This paper tackles the design and evaluation of cost sensitive Support Vector Machine (2C-SVM) based radar detectors in presence of Gaussian and K-Distributed clutter. 2C-SVM based solutions are able to approximate the Neyman-Pearson detector for a specific false alarm rate (\(P_{FA}\)). Real data acquired in different wind conditions by a coherent, pulsed and X-Band radar were considered. A statistical analysis is carried out to design the 2C-SVM for detecting targets with unknown parameters in Gaussian and non-Gaussian interference. A grid search of the best training parameters to approximate the pair detection probability (\(P_D\)) and \(P_{FA}\) of the NP detector is required. Results prove the capability of the 2C-SVM based detectors to maximize the \(P_D\) for a desired \(P_{FA}\) independently of the detection problem likelihood functions. more...

The mean-shift (MS) algorithm is applied for reducing speckle noise and segmenting synthetic aperture radar (SAR) images. Two coastal images acquired by Envisat's advanced SAR (ASAR) [European Space Agency (ESA)] are used. Studies of the MS parameters are carried out according to the desired product: a speckle filtered image where textures and edges are preserved, or a segmented image, where land and sea are distinguished, as a previous stage for obtaining a land mask and detecting the coastal line. In all cases, Gaussian kernels are used. Speckle filtering results are compared with those obtained using uniform kernels, proving that the former provides better results than the latter. A segmentation approach based on the positions and frequencies at which the MS converges is applied. The use of a combined spatial-range processing and the corresponding bandwidths makes the MS suitable for the two proposed problems. The solid theoretical basis of this procedure allows designing a guided search of the best parameters according to the desired solution, avoiding a tedious trial-and-error process. Although the used images have different characteristics, results prove that similar sets of parameters can be used, showing some degree of robustness with respect to the image, for a given sensor and image acquisition mode. more...

The detection of Swerling 0 targets in movement in sea-ice Weibull-distributed clutter by neural networks (NNs) is presented in this paper. Synthetic data generated for typical sea-ice Weibull parameters reported in the literature are used. Due to the capability of NNs for learning the statistical properties of the clutter and target signals during a supervised training, high clutter reduction rates are achieved, reverting on high detection performances. The proposed NN-based detector is compared with a reference detector proposed in the literature that approximates the Neyman-Pearson (NP) detector. The results presented in the paper allow empirically demonstrating how the NN-based detector outperforms the detector taken as reference in all the cases under study. It is achieved not only in performance but also in robustness with respect to changes in sea-ice Weibull-distributed clutter conditions. Moreover, the computational cost of the NN-based detector is very low, involving high signal processing speed. more...

The detection of Gaussian signals with an unknown correlation coefficient rhos is considered. Solutions based on neural networks (NNs) are studied, and a strategy for designing committee machines in a composite hypothesis test is proposed. A single multilayer perceptron (MLP) has been trained with rhos uniformly varying in [0, 1]. Considering the decision boundaries for rhos = 0 and rhos = 1 and how an MLP approximates them, a detection scheme composed of two MLPs has been proposed. One of them MLP1 has been trained with rhos uniformly varying in [0, 0.5], and the other one MLP2 has been trained with rhos uniformly varying in [0.5, 1]. For making a decision, the higher output is compared to a threshold for each false-alarm probability (P FA). This strategy simplifies the task of finding a compromise solution between the computational cost and the approximation error and outperforms the single-MLP detector. When MLP1 is substituted with a radial basis function NN (RBFNN), a new combination strategy of the outputs is required. We propose separately thresholding the outputs and applying them to an or logic function. The performance of this detector is slightly better than the two-MLP one, and the computational cost is significantly reduced. more...

A fast non-parametric CFAR ship detector based on the statistical modeling of sea clutter in SAR images is proposed. Typical CFAR detectors, like the double parameter model (DPM), assume a Gaussian sea clutter model and usually degrade the image resolution using target windows. The proposed detector works in a pixel-by-pixel fashion, adaptively selecting a decision threshold for every single patch the SAR image is divided into. Sea clutter is modeled using the Generalized Gamma distribution. Therefore, the presence of different-sized ships will not become an issue and they will be better characterized, allowing the extraction of the target information, which could be used for refocusing, feature extraction, modeling and classification, while maintaining the resolution of the SAR image. more...

This paper tackles the evaluation of radar detectors with real data in a scenario composed by targets with unknown Doppler shift and sea clutter. A Neural Network-based Constant False Alarm Rate (CFAR) technique, NN-CFAR, is compared with reference detection schemes based on Doppler processors and conventional CFAR detectors. In these reference solutions, although CFAR techniques are designed for a desired false alarm rate, PFA, we prove that the final PFA rate is higher than the desired one. In this paper, a detection performance improvement is obtained with a detector that is a better approximation to the Neyman-Pearson detector based on the generalized Likelihood Ratio (selecting the maximum filter bank output), and uses a unique CFAR detector. Due to the non-linear nature of the maximum function, conventional CFAR detectors are not suitable. The improved detector is designed and applied to real data acquired by a coherent and pulsed radar system at X-band frequencies. Results prove that the NN-CFAR provides a higher probability of detection while fulfilling the PFA requirement. more...

This paper tackles a statistical analysis of bistatic sea radar clutter data acquired by an experimental demonstrator developed by the University of Alcala, based on DVB-T signals. The selected scenario is located at the Military Naval School of Marin, in the Spanish North-west coast. Goodness-off-it techniques are used to fit the empirical cumulative distribution function to theoretical models, and the one-lag correlation coefficient is estimated. Results prove that a Gaussian clutter model can be assumed for high Doppler shifts. However, the zero Doppler shift and values close to it present high variability, so a non-homogeneous clutter characterization is required. The acquisition radar matrix is correlated along the range dimension and uncorrelated along the Doppler one. more...