Iet Radar Sonar and Navigation最新文献

The authors propose a multi-agent, multi-dimensional joint optimisation decision-making strategy to tackle the challenges jammers encounter when interfering with multi-functional radars, which possess advanced anti-interference capabilities. The strategy is divided into optimising the interference style and three parameters: timing, power, and duration, to enhance interference effectiveness. Furthermore, state value reuse is combined with the duelling double deep Q-learning and multi-agent deep deterministic policy gradient algorithms to effectively manage the multi-dimensional optimisation of the interference strategy. Simulation results demonstrate that the proposed algorithm outperforms Ant-QL, heuristic accelerated Q-learning, and asynchronous advantage actor-critic algorithms in terms of convergence speed and stability. It identifies a more efficient strategy for transitioning the radar from its initial state to the state with the lowest threat level to the jammer, achieving a 24% improvement in convergence speed. Additionally, the performance curve exhibits better stability.

The problem of detecting the direction of range-spread targets in the presence of subspace interference, along with homogeneous and partially homogeneous Gaussian clutter backgrounds characterised by an unknown persymmetric covariance matrix, is being investigated. It is assumed that the interference subspace is linearly independent of the signal subspace, and the coordinates of both subspaces are unknown. Leveraging the property of persymmetry, the two-step Generalised Likelihood Ratio Test and the two-step Wald test are proposed to formulate three detectors in the presence of subspace interference, homogeneous, and partially homogeneous Gaussian clutter. Theoretical derivations and simulations demonstrate that three proposed detectors maintain a constant false alarm rate with respect to the unknown clutter covariance matrix. In comparison to existing detectors in similar backgrounds, particularly in scenarios with limited training data, these three detectors exhibit superior detection performance.

Reconfigurable intelligent surface (RIS) refers to a two-dimensional smart surface consisting of massive number of reflecting elements. Both active RIS (ARIS) and passive RIS (PRIS) are promising technologies that can adapt and reconfigure the wireless environment, enhancing the reliability and capacity of wireless networks. The authors focus on enhancing the detection ability of ARIS/PRIS-aided multiple-input-multiple-output radar system in the presence of signal-dependent clutter. Constant-envelope constraint is imposed on the sought radar waveforms to improve the practicability of the radar system. To tackle the resultant non-convex problem, a cyclic method based on minorisation–maximisation and alternating direction method of multipliers is derived to iteratively optimise the receive filters, the transmit waveforms, and the RIS coefficients. The major finding is that the distance between the radar and the ARIS has little to no impact on the radar signal-to-interference-plus-noise ratio (SINR). For the PRIS-aided radar system, a simplified model can significantly improve the operational efficiency and has little impact on the radar SINR. Numerous results verify the effectiveness of the proposed algorithm.

Rotor unmanned aerial vehicles (UAVs) play an important role in both military and civilian fields nowadays. The safety risks associated with the UAVs increase the urgent need for detecting UAVs in urban environments as well. Moreover, UAVs are easily located in the non-line-of-sight (NLOS) building sheltered area relative to the radar, making it very challenging to detect and localise. A novel algorithm for localising the rotor UAV in the common L-shaped street building sheltered area is proposed. First, the authors establish a multipath signal model for a rotor UAV hovering over an L-shaped street scene, leveraging the frequency-modulated continuous wave signal. Then, the multipath information of the UAV is extracted by identifying the rotating periodicity of the blade embedded in the time-frequency spectrum of the received signal. The back projection imaging is then conducted on the UAV-related multipath. After extracting multipath ghosts in the image, the street area, where the UAV locates, can be determined, and the UAV is further localised using the path reflection characteristics of this area. Simulations and practical experiments based on millimetre waves indicate that the proposed method can enable high-accuracy estimation of rotor UAV in the NLOS building sheltered area.

The authors analyse the sequential lobing radar (SLR) resistance against the scan rate modulation (SRM) jamming technique. Unlike previous studies, the authors analyse SLRs with sinc antenna patterns, enabling investigation of the sidelobe region's vulnerability. By incorporating second-order angular tracking loops (SOATLs), the first analysis of break-lock probability for SLRs under SRM jamming is introduced. The analysis reveals the influence of SOATL parameters (damping ratio and natural frequency) on both angular root-mean-square-error at low jamming-to-signal-ratio (JSR) region and break-lock probability at high JSR region. Additionally, the impact of squint angle on SLR resistance to SRM jamming is examined. Furthermore, the optimal duty cycle as a function of JSR, which maximises break-lock probability is presented. Significantly, the theoretical results support the 20 dB JSR requirement for SRM effectiveness, often cited experimentally in literature, and extend the theoretical analysis of the SRM technique carried out for the main lobe region of SLRs. This finding bridges the gap between theoretical analysis and practical observations.

The analysis of the Armed Forces (AF) operational capabilities requires the construction of a formal model. Elements of this model will be presented here. Including selected aspects of Electronic Warfare (EW) in an operational capability assessment model is an important and difficult task. The essence of the impact of radio-electronic, like other forms of cyber warfare, on reconnaissance, command and communications systems is to hinder or prevent kinetic operations. The model should identify and prioritise the required capabilities by defining the key objectives: identification of the future security environment and within it the operational environment, identification of planning scenarios and requirements for future forces, including forces to execute EW, identification of specific tasks in relation to AF missions and tasks, Identification of the list of AF required capabilities in the AF capability catalogue. The idea of identifying required capabilities and identifying gaps is presented in this chapter. The key questions/problems posed in the analysis process are: Do the identified capabilities fit with the mission and operational concepts and threats? What are the indicators for achieving the desired operational capabilities? What might be the cost of providing the AF with the required capabilities? What is the key approach to address these issues? An operational capability approach to planning is used, including the identification of the AF' reference modules, including EW units. Dimensioning of operational capabilities using formal and simulation methods is an important problem. An optimisation model is presented for determining the structure of the AF, based on reference modules with desired capabilities, enabling the realisation of identified operational concepts, taking into account the following criteria: operational and cost. The analysis proposes custom simulation models, based on mathematical models of the AF. The simulation is based on a step-by-step analysis with an introduced scenario and possible enemy structure and defined mission. A way of modifying the assessment of the parties' potentials as a result of the EW impact is presented. This has implications for the allocation of reference units in the formation of own forces in response to the enemy's potential formation and action.

The critical role of specifying micro-Doppler mode performance in the modelling and development of modern radar systems is investigated. The authors focus on the detection of micro-Doppler modulation from light aircraft, analysing data from eight helicopters and nine propeller aircraft. With the growing need for accurate target classification in radar technology, incorporating micro-Doppler detection metrics into radar performance specifications has become increasingly important. This research offers a novel approach to measuring the detectability of micro-Doppler modulation relative to returns from the main fuselage. The investigation covers the impacts of various preprocessing techniques, polarisation, and aspect angle on detection capabilities. Findings reveal that, on average, micro-Doppler modulation from propellers is detectable at distances between 50% and 100% of the range at which the fuselage is detected. For helicopters, this range decreases to between 30% and 80%. Additionally, the study introduces empirically derived statistical models designed to predict micro-Doppler detection ranges in relation to fuselage returns, enhancing the predictability and specificity of radar system performance. This novel contribution presents a basis for improving radar system specifications, leading ultimately to more predictable and reliable light aircraft classification.

Drone surveillance with multi-function radar (MFR) can benefit a lot from the careful radar pulse train organisation into dedicated sub-RPTs serving particular needs of tasks. In contemporary scenarios of MFR applications, where navigation, search and rescue, and natural environment safeguarding are to be shared, of particular importance is a case where airborne small drone detection radar performs other tasks concurrently. Resource sharing within the radar unit is based on variables and unpredictable circumstances, leading to strains in resources in MFR. Consequently, such constraints limit MFR functioning with optimal drone sensitivity for its own sake. To ensure a high quality of radar services performed quickly, with a low DC power consumption, the task sharing approach by the common MFR platform, non-periodic bursts emission of radar pulse energy has gained our major attention. At the same time, it was assumed that bursts feature periodic time intervals between radar pulses, which is a favourable circumstance in the control and implementation of signal processing. Each sub-RPTs is designed to cope with particular detection tasks. One to four linear polarisations (VV, VH, HV, HH) are activated. The focus of the investigation was on the radar emitting a few thousand pulses per second, but only a few 10 pulses per second were expected to be required to detect small airborne drones. The core of the research study was the optimisation process of the scheme operating with 4 to 16 pulse bursts optimised for drone detection with a modest use of resources at MFR. While performing several activities, the X-band MFR platform called ENAVI was developed in-house. The proposed non-periodic burst scheme optimisation approach was validated with in-field tests with the ENAVI radar model. The in-air target was a 3-metre fixed-wing drone having low RCS and flying at different altitudes with a speed close to 200 km/h. The radar antenna was a 26 dBi low-profile dual-polarisation array making it feasible to detect drones remaining a few degrees off the antenna breadboard direction. A very high likelihood of detection of drones from a few kilometres distance was demonstrated within one second. The authors present the effectiveness of the cell-averaging technique which proved to correctly detect drones within a 7-km range, and how MFR radar echoes can be used for basic weather surveillance. One vertical VV polarisation was used for drone detection and two VV and VH polarisations for weather observation. Weather radar capabilities were examined against heavy rain clouds imposing a hazard to the safety of drone flights.

It has become an interesting topic for modern radar possessing capabilities of polarimetric measurement, high-resolution imaging, and good delay-Doppler resolution. The linear frequency modulation (LFM) scheme is widely used in radar systems as it can achieve both high Doppler tolerance and resolution. Based on the LFM scheme, a novel waveform is proposed, namely, the orthogonal double V-linear frequency modulation (ODV-LFM), which exhibits the capability to mitigate the influence of delay-Doppler coupling and reduces the risk of false targets and ghosts in multiple-target scenes. Based on the ODV-LFM signal, a simultaneous polarimetric measurement method is proposed to obtain fully polarimetric information of the target. According to the unique chirp rate characteristic of the ODV-LFM signal, the pointwise linear and non-linear processing methods are proposed to enhance delay-Doppler resolution, suppress sidelobes, and achieve high-resolution imaging without substantially compromising the signal detection performance. Finally, simulated experiments are conducted to demonstrate the superiority of the proposed waveform and methods.

The authors address the problem of observability analysis and enhancement for missiles equipped with strapdown seekers, especially considering the line-of-sight angle-only measurements and the constraints on impact angle and terminal acceleration. First, based on the generalised polynomial chaos expansion, a novel data-driven observability analysis method is proposed to quantitatively analyse the observability of the radome aberration estimation system in real time, including the observability condition, the observability degree of each state and the effect of stochastic noises. The results show that under conventional proportional navigation guidance, the radome aberration estimation system is weakly observable with line-of-sight angle-only measurements. To address this problem, a novel manoeuvre algorithm, the observability-enhanced guidance law, is introduced to enhance the system observability within specified constraints, thereby improving the estimation performance. This guidance law incorporates a bias term to meet terminal constraints, and optimises the navigation gain using the proposed observability indices. Simulations are conducted to verify the performance of the proposed guidance law in conjunction with a target state estimator.