43 research outputs found

    Fusion of deep representations in multistatic radar networks to counteract the presence of synthetic jamming

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    Micro-Doppler signatures are extremely valuable in the classification of a wide range of targets. This paper investigates the effects of jamming on the micro-Doppler classification performance and explores a potential deep topology enabling low-bandwidth data fusion between nodes in a multistatic radar network. The topology is based on an array of three independent deep neural networks (DNNs) functioning cooperatively to achieve joint classification. In addition to this, a further DNN is trained to detect the presence of jamming, and from this, it attempts to remedy the degradation effects in the data fusion process. This is applied to the real experimental data gathered with the multistatic radar system, NetRAD, of a human operating with seven combinations of holding a rifle-like object and a heavy backpack that is slung on their shoulders. The resilience of the proposed network is tested by applying synthetic jamming signals into specific radar nodes and observing the networks' ability to respond to these undesired effects. The results of this are compared with a traditional voting system topology, serving as a convenient baseline for this paper

    Fusion of Deep Representations in Multistatic Radar Networks to Counteract the Presence of Synthetic Jamming

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    Micro-Doppler signatures are extremely valuable in the classification of a wide range of targets. This work investigates the effects of jamming on micro-Doppler classification performance and explores a potential deep topology enabling low bandwidth data fusion between nodes in a multistatic radar network. The topology is based on an array of three independent deep neural networks (DNNs) functioning cooperatively to achieve joint classification. In addition to this, a further DNN is trained to detect the presence of jamming and from this it attempts to remedy the degradation effects in the data fusion process. This is applied to real experimental data gathered with the multistatic radar system NetRAD, of a human operating with seven combinations of holding a rifle-like object and a heavy backpack which is slung on their shoulders. The resilience of the proposed network is tested by applying synthetic jamming signals into specific radar nodes and observing the networks’ ability to respond to these undesired effects. The results of this are compared with a traditional voting system topology, serving as a convenient baseline for this work

    Increasing Combat Aircraft Survivability Through Coherent Self-Protection Jammers

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    When the battlefields were within the visual range, the objective of deception tactics in warfare was to deceive the human senses. In the battlefield of electromagnetic spectrum, the objective of deception is to deceive the sensors of the enemy weapon systems. The survivability of the aircraft operating in hostile environment is of prime importance to the mission planner. If the aircraft can deny its location information to the tracking radar of the radar guided threat missile system, this, in return, may increase its survivability. The deception, a tactic which stems from the wisdom of ancient battles, incarnated in the form of Electronic Attack (EA) can give this capability to the aircraft operating in a hostile environment. Self-Protection Jammers (SPJs) mounted on aircraft that employ deception-repeater jamming techniques and the resulting effect of the deception jamming on the enemy sensor systems will be examined in this study. The impact of the specific flight path and formation geometry should be considered both from the perspective of coherent SPJs effectiveness and the survivability. The individual effectiveness of the EA by SPJs is usually limited by the available Effective Radiated Power (ERP). Due to limitations on the size of the aircraft, one can not afford to build powerful SPJs. The jamming technique and the effect of multiple jammers with respect to jamming effectiveness need to be examined for mission planning analysis. The specific jamming technique evaluated is the combined Range Gate Pull-Off (RGPO) and Velocity Gate Pull-Off (VGPO) against pulse Doppler radar. The challenge is to decide the least vulnerable flight path and the formation geometry for a strike formation in an air-to-ground engagement scenario. The degree of survivability provided by the combination of the formation geometry, flight path and the EA (multiple spatially dispersed coherent jammers) is the focus of this research. The modeling and simulation of the interactions between the self-protection jammer and the pulse Doppler tracking radar with respect to formation geometry and flight path is the initial objective

    Non-Cooperative Detection of Frequency-Hopped GMSK Signals

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    Many current and emerging communication signals use Gaussian Minimum Shift Keyed (GMSK), Frequency-Hopped (FH) waveforms to reduce adjacent-channel interference while maintaining Low Probability of Intercept (LPI) characteristics. These waveforms appear in both military (Tactical Targeting Networking Technology, or TTNT) and civilian (Bluetooth) applications. This research develops wideband and channelized radiometer intercept receiver models to detect a GMSK-FH signal under a variety of conditions in a tactical communications environment. The signal of interest (SOI) and receivers have both fixed and variable parameters. Jamming is also introduced into the system to serve as an environmental parameter. These parameters are adjusted to examine the effects they have on the detectability of the SOI. The metric for detection performance is the distance the intercept receiver must be from the communication transmitter to meet a given set of intercept receiver performance criteria (e.g., PFA and PD). It is shown that the GMSK-FH waveform benefits from an increased hop rate, a reduced signal duration, and the introduction of jitter into the waveform. Narrowband jamming is also very detrimental to channelized receiver performance. The intercept receiver benefits from reducing the bandwidth of the channelized radiometer channels, although this requires precise a priori knowledge of the hop frequencies

    GNSS-based passive radar techniques for maritime surveillance

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    The improvement of maritime traffic safety and security is a subject of growing interest, since the traffic is constantly increasing. In fact, a large number of human activities take place in maritime domain, varying from cruise and trading ships up to vessels involved in nefarious activities such as piracy, human smuggling or terrorist actions. The systems based on Automatic Identification System (AIS) transponder cannot cope with non-cooperative or non-equipped vessels that instead can be detected, tracked and identified by means of radar system. In particular, passive bistatic radar (PBR) systems can perform these tasks without a dedicated transmitter, since they exploit illuminators of opportunity as transmitters. The lack of a dedicated transmitter makes such systems low cost and suitable to be employed in areas where active sensors cannot be placed such as, for example, marine protected areas. Innovative solutions based on terrestrial transmitters have been considered in order to increase maritime safety and security, but these kinds of sources cannot guarantee a global coverage, such as in open sea. To overcome this problem, the exploitation of global navigation satellites system (GNSS) as transmitters of opportunity is a prospective solution. The global, reliable and persistent nature of these sources makes them potentially able to guarantee the permanent monitoring of both coastal and open sea areas. To this aim, this thesis addresses the exploitation of Global Navigation Satellite Systems (GNSS) as transmitters of opportunity in passive bistatic radar (PBR) systems for maritime surveillance. The main limitation of this technology is the restricted power budget provided by navigation satellites, which makes it necessary to define innovative moving target detection techniques specifically tailored for the system under consideration. For this reason, this thesis puts forward long integration time techniques able to collect the signal energy over long time intervals (tens of seconds), allowing the retrieval of suitable levels of signal-to-disturbance ratios for detection purposes. The feasibility of this novel application is firstly investigated in a bistatic system configuration. A long integration time moving target detection technique working in bistatic range&Doppler plane is proposed and its effectiveness is proved against synthetic and experimental datasets. Subsequently the exploitation of multiple transmitters for the joint detection and localization of vessels at sea is also investigated. A single-stage approach to jointly detect and localize the ship targets by making use of long integration times (tens of seconds) and properly exploiting the spatial diversity offered by such a configuration is proposed. Furthermore, the potential of the system to extract information concerning the detected target characteristics for further target classification is assessed

    Development and Evaluation of a Multistatic Ultrawideband Random Noise Radar

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    This research studies the AFIT noise network (NoNET) radar node design and the feasibility in processing the bistatic channel information of a cluster of widely distributed noise radar nodes. A system characterization is used to predict theoretical localization performance metrics. Design and integration of a distributed and central signal and data processing architecture enables the Matlab®-driven signal data acquisition, digital processing and multi-sensor image fusion. Experimental evaluation of the monostatic localization performance reveals its range measurement error standard deviation is 4.8 cm with a range resolution of 87.2(±5.9) cm. The 16-channel multistatic solution results in a 2-dimensional localization error of 7.7(±3.1) cm and a comparative analysis is performed against the netted monostatic solution. Results show that active sensing with a low probability of intercept (LPI) multistatic radar, like the NoNET, is capable of producing sub-meter accuracy and near meter-resolution imagery

    Spectrum sensing for cognitive radio and radar systems

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    The use of the radio frequency spectrum is increasing at a rapid rate. Reliable and efficient operation in a crowded radio spectrum requires innovative solutions and techniques. Future wireless communication and radar systems should be aware of their surrounding radio environment in order to have the ability to adapt their operation to the effective situation. Spectrum sensing techniques such as detection, waveform recognition, and specific emitter identification are key sources of information for characterizing the surrounding radio environment and extracting valuable information, and consequently adjusting transceiver parameters for facilitating flexible, efficient, and reliable operation. In this thesis, spectrum sensing algorithms for cognitive radios and radar intercept receivers are proposed. Single-user and collaborative cyclostationarity-based detection algorithms are proposed: Multicycle detectors and robust nonparametric spatial sign cyclic correlation based fixed sample size and sequential detectors are proposed. Asymptotic distributions of the test statistics under the null hypothesis are established. A censoring scheme in which only informative test statistics are transmitted to the fusion center is proposed for collaborative detection. The proposed detectors and methods have the following benefits: employing cyclostationarity enables distinction among different systems, collaboration mitigates the effects of shadowing and multipath fading, using multiple strong cyclic frequencies improves the performance, robust detection provides reliable performance in heavy-tailed non-Gaussian noise, sequential detection reduces the average detection time, and censoring improves energy efficiency. In addition, a radar waveform recognition system for classifying common pulse compression waveforms is developed. The proposed supervised classification system classifies an intercepted radar pulse to one of eight different classes based on the pulse compression waveform: linear frequency modulation, Costas frequency codes, binary codes, as well as Frank, P1, P2, P3, and P4 polyphase codes. A robust M-estimation based method for radar emitter identification is proposed as well. A common modulation profile from a group of intercepted pulses is estimated and used for identifying the radar emitter. The M-estimation based approach provides robustness against preprocessing errors and deviations from the assumed noise model

    Electronic warfare technology

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    An analysis of the modern technology employed in Electrical Warfare systems is carried out. Electronic and optical techniques presently used in the detection, localization, processing and identification of signals, linked with active and passive countermeasures and countercountermeasures, are analyzed. "Seal-world" designs and configurations are discussed with respect to effectiveness, reliability and designs and operational trade-offs. Topics are divided according the modern classification of Electronic Warfare, covering confusion reflectors, masking and deceiver jammers, intercept receivers as well as the new field of Electro-Optical Electronic Warfare. special characteristics inherent to the Surface Navy are pointed out. In the Appendices, the experiment of a circuit devised to be useful in signal recognition is described, and a list of missiles with electronic and guidance characteristics is presented.http://archive.org/details/electronicwarfar00bittLieutenant Commander, Brazilian NavyApproved for public release; distribution is unlimited

    Space-time adaptive processing techniques for multichannel mobile passive radar

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    Passive radar technology has reached a level of maturity for stationary sensor operations, widely proving the ability to detect, localize and track targets, by exploiting different kinds of illuminators of opportunity. In recent years, a renewed interest from both the scientific community and the industry has opened new perspectives and research areas. One of the most interesting and challenging ones is the use of passive radar sensors onboard moving platforms. This may offer a number of strategic advantages and extend the functionalities of passive radar to applications like synthetic aperture radar (SAR) imaging and ground moving target indication (GMTI). However, these benefits are paid in terms of motion-induced Doppler distortions of the received signals, which can adversely affect the system performance. In the case of surveillance applications, the detection of slowly moving targets is hindered by the Doppler-spread clutter returns, due to platform motion, and requires the use of space-time processing techniques, applied on signals collected by multiple receiving channels. Although in recent technical literature the feasibility of this concept has been preliminarily demonstrated, mobile passive radar is still far from being a mature technology and several issues still need to be addressed, mostly connected to the peculiar characteristics of the passive bistatic scenario. Specifically, significant limitations may come from the continuous and time-varying nature of the typical waveforms of opportunity, not suitable for conventional space-time processing techniques. Moreover, the low directivity of the practical receiving antennas, paired with a bistatic omni-directional illumination, further increases the clutter Doppler bandwidth and results in the simultaneous reception of non-negligible clutter contributions from a very wide angular sector. Such contributions are likely to undergo an angle-dependent imbalance across the receiving channels, exacerbated by the use of low-cost hardware. This thesis takes research on mobile passive radar for surveillance applications one step further, finding solutions to tackle the main limitations deriving from the passive bistatic framework, while preserving the paradigm of a simple system architecture. Attention is devoted to the development of signal processing algorithms and operational strategies for multichannel mobile passive radar, focusing on space-time processing techniques aimed at clutter cancellation and slowly moving target detection and localization. First, a processing scheme based on the displaced phase centre antenna (DPCA) approach is considered, for dual-channel systems. The scheme offers a simple and effective solution for passive radar GMTI, but its cancellation performance can be severely compromised by the presence of angle-dependent imbalances affecting the receiving channels. Therefore, it is paired with adaptive clutter-based calibration techniques, specifically devised for mobile passive radar. By exploiting the fine Doppler resolution offered by the typical long integration times and the one-to-one relationship between angle of arrival and Doppler frequency of the stationary scatterers, the devised techniques compensate for the angle-dependent imbalances and prove largely necessary to guarantee an effective clutter cancellation. Then, the attention is focused on space-time adaptive processing (STAP) techniques for multichannel mobile passive radar. In this case, the clutter cancellation capability relies on the adaptivity of the space-time filter, by resorting to an adjacent-bin post-Doppler (ABPD) approach. This allows to significantly reduce the size of the adaptive problem and intrinsically compensate for potential angle-dependent channel errors, by operating on a clutter subspace accounting for a limited angular sector. Therefore, ad hoc strategies are devised to counteract the effects of channel imbalance on the moving target detection and localization performance. By exploiting the clutter echoes to correct the spatial steering vector mismatch, the proposed STAP scheme is shown to enable an accurate estimation of target direction of arrival (DOA), which represents a critical task in system featuring few wide beam antennas. Finally, a dual cancelled channel STAP scheme is proposed, aimed at further reducing the system computational complexity and the number of required training data, compared to a conventional full-array solution. The proposed scheme simplifies the DOA estimation process and proves to be robust against the adaptivity losses commonly arising in a real bistatic clutter scenario, allowing effective operation even in the case of a limited sample support. The effectiveness of the techniques proposed in this work is validated by means of extensive simulated analyses and applications to real data, collected by an experimental multichannel passive radar installed on a moving platform and based on DVB-T transmission
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