Radar Network System Research Articles

Collaborative trajectory planning and transmit resource scheduling for multiple target tracking in distributed radar network system with GTAR

A reasonable resource management strategy can maximize the sensing performance of radar network system via adaptively controlling the working parameters of interest. In this paper, a collaborative trajectory planning and transmit resource scheduling (CTPTRS) strategy for multiple target tracking (MTT) in distributed radar network system with ground-based transmitters and airborne receivers (GTAR) is proposed. Firstly, the CTPTRS for the distributed radar network with GTAR (DRN-GTAR) is formulated as a non-convex optimization problem. To be more precise, the transmit power with the bandwidth of each transmitter and the trajectory of each airborne front-receiver are controlled jointly and adaptively to maximize the MTT performance. Secondly, to tackle the non-convex optimization problem, an efficient two-stage solution technique integrated with the semi-definite programming (SDP), the Latin hypercube sampling-based stochastic simulation (LHS) and the improved particle swarm optimization-tabu search (IPSOTS) is proposed. Finally, simulation results demonstrate the effectiveness of the proposed CTPTRS strategy. Furthermore, in terms of the MTT performance, the proposed strategy owns superior performance compared with six other existing baseline strategies.

Space Target Recognition Based on Radar Network Systems with BiGRU-Transformer and Dual Graph Fusion Network

Space Target Recognition Based on Radar Network Systems with BiGRU-Transformer and Dual Graph Fusion Network

Reinforcement Learning-Based Low-Altitude Path Planning for UAS Swarm in Diverse Threat Environments

Unmanned aircraft systems (UASs) with autonomous maneuvering decision capabilities are expected to play a key role in future unmanned systems applications. While reinforcement learning has proven successful in solving UAS path planning problems in simple urban environments, it remains under-researched for some complex mountain environments. In this paper, the path planning of UAS swarm for the low-altitude rapid traverse in diverse environments is studied when facing the threats of complex terrain, radars and swarm failure. First, a UAS swarm radar detection probability is built up for evaluating the radar detection threat by a networked radar system, where the detection probability of a UAS swarm is equated to a single UAS with appropriate position and radar cross section named as the swarm virtual leader. Second, a reinforcement learning based path planning method is proposed to seek the optimal path for the swarm virtual leader which balances instantaneous reward, including detection probability and path constraints with terminal reward, including normal rate. Third, a formation optimization strategy is designed to further reduce the threat of radar detection through dynamically adjusting the formation geometry. Final, simulations in the complex environment have been carried out to evaluate the performance of the proposed method, where the path quality, task success rate and normal rate are counted as the performance indicators.

An improved harmonics suppression power amplifier circuit using integrated self‐resonant capacitor for radar application

SummaryIn order to ensure that the electromagnetic compatibility and mutual interference of multiple radar network systems meet the requirements, a 55‐W gallium nitride (GaN) high harmonics suppression (HSs) high power amplifier (HPA) microwave monolithic integrated circuit (MMIC) with an operating frequency of 5.1–6.3 GHz is designed for radar network system. An HSs method using self‐resonant capacitor integrated in the output matching network of HPA is proposed to improve the HSs characteristics. The measured results show that under the condition of 100‐μs pulse width and 10% duty cycle, the HSs are greater than 48 dBc while the output power is greater than 55 W, the power gain is 21 dB, and the power additional efficiency (PAE) is 54%, which is suitable for use in radar network system. The size of the HPA is 3.55 × 4.05 mm2.

Asynchronous Track-to-Track Association Based on Pseudo Nearest Neighbor Distance for Distributed Networked Radar System

In radar network systems, target tracks reported from different radars need to be associated and fused, and the track-to-track association (TTTA) effect is a key factor that directly affects the performance of the entire system. In order to solve the problem of the low accuracy of TTTA in network radar systems with asynchronous unequal rates, an asynchronous TTTA algorithm based on pseudo nearest neighbor distance is proposed. Firstly, the calculation method of pseudo nearest neighbor distance between the track point and the track data set is defined, then the correlation degree between the two track data sets is obtained by using grey theory, and then the Jonker-Volgenant algorithm is combined with the classical allocation method to judge the TTTA. The algorithm does not need time domain alignment and can effectively avoid the accumulation and propagation of estimation errors. The simulation results show that the algorithm has a high average correct association rate and is less affected by the radar sampling period ratio, startup time, and noise distribution, and the average correct association rate for different movement types of target tracks remains above 99%. Furthermore, compared with other algorithms, this algorithm maintains a stable low level of the number of false associations and the maximum false association rates, and has strong robustness and advantages.

Range Deception Jamming Performance Evaluation for Moving Targets in a Ground-Based Radar Network

With the rapid development of electronic information technology, the forms and technologies of electronic warfare have become more complicated, and electronic countermeasures (ECMs) and electronic counter-countermeasures (ECCMs) have become fierce in recent years. Networked radars have become an important means of ECMs due to their “four anti-resistance performance” against electronic jamming, anti-stealth, anti-radiation missiles, and low-altitude penetration. Based on this, this paper evaluates the performance of range deception jamming on an air-based jammer in a ground-based radar network. In this paper, the ground-based radar coordinate system conversion relationship is first established. Then, the statistical variance data fusion criterion for the radar network is constructed. Hence, based on the data fusion criterion, the jamming range delay boundary and the radar position information are recorded. Finally, the jamming performance evaluation can be achieved by analyzing the relationship between the jamming range delay and the radar position. The results of the simulated experiments reveal that when the jamming range delay is sufficiently small, the radar network system can be interfered with successfully by the range false target.

Sequential Fusion Based Approach for Estimating Range Gate Pull-Off Parameter in a Networked Radar System: An ECCM Algorithm

Networked radar is an emerging and effective alternative to traditional radar systems to provide improved performance by fusing information from multiple radars. Further, networked radar systems (NRS) have found numerous deployments in military and civilian infrastructures in recent years. Electronic countermeasures (ECM) like jamming, Range Gate Pull-Off (RGPO), and Velocity Gate Pull-Off (VGPO) generally pose a high risk to the radar systems by injecting intentional interference. This paper proposes networked radar to detect the RGPO ECM attack and estimate the range gate deception parameter of the deceived local track in an NRS. Each radar comprises a local tracker to provide the local estimates (updated state and updated covariance), and these estimates are then sent to the fusion node. Thereafter, a track-to-track association (T2TA) is formulated at the fusion node to detect the deceived tracks using all the available local tracks. For the deceived track, the pseudo-measurements are created using the inverse Kalman filter-based tracklets. All the local tracks except deceived track are compensated and sequentially fused to create a reference measurement. After that, the deception parameter of the deceived track is estimated by using pseudo-measurement and the reference measurement by employing the recursive least square estimator (RLSE). In addition, the proposed algorithm is analyzed for single and multiple RGPO based ECM scenarios. Further, the Cramer Rao Lower Bound (CRLB) for the proposed methodology is derived. The results are quantified with a Position Root Mean Square Error (PRMSE), CRLB, innovation test, normalized estimation error squared (NEES) test, and confidence interval. The simulation results demonstrate that the proposed estimation technique provides good performance in the presence of all the local tracks are being attacked by RGPO ECM. Besides, it is evident from the results that estimator efficiency is falling below the 5% tail probability of the chi-square distribution.

Joint Detection Threshold Optimization and Illumination Time Allocation Strategy for Cognitive Tracking in a Networked Radar System

In this paper, a joint detection threshold optimization and illumination time allocation (JDTOITA) strategy was developed for multi-target tracking in an asynchronous networked radar system under cluttered background. The basis of this strategy is to facilitate detection and tracking using the prior target information in the tracking recursive cycle. The information reduction factor in the Bayesian detection framework is derived, optimized, and incorporated in the posterior Cramer-Rao lower bound (PCRLB), which is then utilized to serve as the optimization metric. Due to the asynchronous data and cluttered environment, the objective function needs to be recursively deduced and is nonlinear and nonconvex. We propose an efficient solver integrating the convex relaxation with the local search technique for this problem solving. Simulation results demonstrate the superiority of the JDTOITA strategy compared with the benchmarks with no optimization or optimization of either the illumination time allocation (ITA) or detection threshold alone. The results also imply that the target reflectivity and sampling interval of local radars are two important factors that influence the resource optimization.

Reliable Task Planning of Networked Devices as a Multi-Objective Problem Using NSGA-II and Reinforcement Learning

Tracking and detecting multiple objects is difficult for a single radar device, as it may not have the capacities such as anti-interference and anti-stealth. However, if radar devices of diverse capabilities can be combined to realize collaborative networked operation, the reliability and performance of a radar system in a complex environment can be significantly improved. This paper classify the networked radar-based multi-objective task planning as a combinatorial optimization problem with constraints and abstract a distributed multi-agent system (MAS) model from a networked radar system. A node-selection algorithm was designed based on a greedy policy to narrow down solution space for subsequent networked radar task planning, reduce the amount of calculation, and improve the efficiency of the proposed algorithm. Moreover, focusing on NSGA-II, the proposed algorithm was modified using self-adaptive operators and reinforcement learning. A dual-population strategy was introduced to allow exchanges of multiple individuals between populations during migration, and the number of individuals for the exchange was obtained through reinforcement learning. In this paper, five algorithms are compared and analyzed. In addition, statistical analyses are conducted from four perspectives: the average evaluation value of energy consumption and bandwidth in the Pareto front solutions, the time consumption of the algorithm, and the diversity of the population. The results indicate that among those algorithms, the reinforcement-learning-based RNSGA-II algorithm can produce the best outcomes for networked radar task planning.

Tiresias: A low-cost networked UWB radar system for in-home monitoring of dementia patients.

This paper describes Tiresias, a low-cost, unobtrusive networked radar system designed to monitor vulnerable patients in domestic environments and provide high quality behavioural and health data. Dementia is a disease that affects millions worldwide and progressively degrades an individual's ability to care for themselves. Eventually most people living with dementia will need to reside in assisted living facilities as they become unable to care for themselves. Understanding the effects dementia has on ability to self-care and extending the length of time people living with dementia can remain living independently are key goals of dementia research and care. The networked radar system proposed in this paper is designed to provide high quality behavioural and health data from domestic environments. This is achieved using multiple radar sensors networked together with their data outputs integrated and processed to produce high confidence measures of position and movement. It is hoped the data produced by this system will both provide insights into how dementia progresses, and also help monitor vulnerable individuals in their own homes, allowing them to remain independent longer than would otherwise be possible.

Resource Allocation for Multitarget Tracking and Data Reduction in Radar Network With Sensor Location Uncertainty

Traditional networked radar systems for target tracking usually suffer from a heavy data processing burden, and do not consider the sensor location uncertainties (SLUs), by assuming that radar locations are known perfectly, which is applicable only for static platforms. In this paper, considering sensors mounted on moving platforms, we propose a joint power allocation and measurement selection (JPAMS) strategy for multitarget tracking and data reduction in radar networks with the SLUs. The mechanism is to optimize the transmitted power and select the propagation paths with informative measurements, simultaneously. First, we adopt a distributed fusion architecture to estimate both states of targets and radars in clutter. Based on the distributed fusion architecture, the predicted conditional Cramér-Rao lower bound (PC-CRLB) considering the SLU and the measurement origin uncertainty is derived. Second, the JPAMS strategy is formulated as a bi-objective optimization problem, where the sum of weighted PC-CRLBs and the number of selected propagation paths are used as the performance metrics with respect to tracking and data reduction. The corresponding optimization is a NP-hard problem containing both continuous and binary variables. Third, to solve this nonconvex problem, we propose a sparsity-enhancing sequential convex programming algorithm. Finally, numerical simulations demonstrate the superiority of the proposed JPAMS strategy over the traditional allocation strategies.

Joint Target Assignment and Resource Optimization Framework for Multitarget Tracking in Phased Array Radar Network

In this article, a joint target assignment and resource optimization (JTARO) strategy is proposed for the application of multitarget tracking in phased array radar network system. The key mechanism of our proposed JTARO strategy is to employ the optimization technique to jointly optimize the target-to-radar assignment, revisit time control, bandwidth, and dwell time allocation subject to several resource constraints, while achieving better tracking accuracies of multiple targets and low probability of intercept (LPI) performance of phased array radar network. The analytical expression for Bayesian Cramér-Rao lower bound with the aforementioned adaptable parameters is calculated and subsequently adopted as the performance metric for multitarget tracking. After problem partition and reformulation, an efficient three-stage solution methodology is developed to resolve the underlying mixed-integer, nonlinear, and nonconvex optimization problem. To be specific, in Step 1, the revisit time for each target is determined. In Step 2, we implement the joint signal bandwidth and dwell time allocation for fixed target-to-radar assignments, which combine the cyclic minimization algorithm and interior point method. In Step 3, the optimal target-to-radar assignments are obtained, which results in the minimization of both the tracking accuracy for multiple targets and the total dwell time consumption of the network system. Simulation results are provided to demonstrate the advantages of the presented JTARO strategy, in terms of the achievable multitarget tracking accuracy and LPI performance of phased array radar network.

Self-aware Power Management for Maintaining Event Detection Probability of Supercapacitor-powered Cyber-physical Systems

In this article, the self-aware power management framework is investigated for maintaining event detection probability of supercapacitor-powered cyber-physical systems, with a radar network system as an example. Maintaining the event detection probability of the radar network is decomposed as a problem of controlling the quality of service of each network node. Then a power management method based on model predictive control and particle swarm optimization is proposed for tracking the reference quality of service of each node while satisfying the operation constraints. The effectiveness of the proposed method is demonstrated through three simulation studies that cover both single node and network scenarios. In addition, to support the proposed power management method, an online state of charge prediction method is developed for the supercapacitor. The online prediction method adopts a supercapacitor model that describes both the ohmic leakage and charge redistribution phenomena and uses online model updating to more accurately capture the supercapacitor behavior and estimate the stored energy.

Low-Cost CMOS Active Array Solution for Highly Dense X-Band Weather Radar Network

This article presents the development of a CMOS active array antenna unit cell as a potential solution for a highly dense, low-altitude short-coverage phased array $X$ -band radar network system. The antenna uses a cross-patch differential feed structure designed in a stacked configuration for bandwidth and cross-polarization enhancement. To overcome the limitations of current CMOS RF performance, a mirroring technique was applied at the element and subarray level. A 16-element array ($4\times 4$ elements), integrated with CMOS T/R modules in a tileable architecture, was developed and characterized. Measured results demonstrate that this proposed array offers cross-polarization levels less than -32 dB across the scanning range of ±45° in the principal planes for dual-polarized alternate transmit and alternate receive (ATAR) phased array weather radar.

Low Probability of Intercept-Based Collaborative Power and Bandwidth Allocation Strategy for Multi-Target Tracking in Distributed Radar Network System

In order to simultaneously enhance the low probability of intercept (LPI) performance and resource utilization of distributed radar network system, an LPI-based collaborative power and bandwidth allocation (CPBA) strategy is developed for multi-target tracking in the current work. The primary aim of the proposed LPI-CPBA strategy is to exploit the optimization technique to minimize the total power consumption of the distributed radar network by collaboratively optimizing the radar node selection, transmit power and signal bandwidth allocation, while satisfying the predetermined tracking accuracies of multiple targets and several resource constraints. The closed-form expression for the predicted Bayesian Cramer-Rao lower bound (BCRLB) incorporating the above controllable parameters is analytically computed and employed to gauge the multi-target tracking performance. Subsequently, an efficient two-stage solution methodology is proposed to solve the resulting mixed-Boolean, non-linear and non-convex optimization problem, which collaboratively determines the radar node selection as well as the transmit power and bandwidth allocation between the designated radar nodes. Extensive numerical simulations are conducted to verify the advantage of the presented LPI-CPBA strategy in terms of the achievable LPI performance of distributed radar network system.

Joint threshold optimization and power allocation of cognitive radar network for target tracking in clutter

Networked radar systems have the ability to enhance the tracking performance by working in a cognitive manner. In the cognitive radar network, resource allocation technique can be employed to improve the system performance. In this paper, a joint threshold optimization and power allocation (JTOPA) strategy for target tracking by radar network in clutter is proposed containing two main stages. At the detection stage, we introduce the Bayesian tracker-aware detector to adaptively adjust the threshold based on the predicted target state information. At the transmitting stage, the limited power resource is optimally assigned to each radar node. By incorporating the improved information reduction factor (IIRF), the Bayesian Cramér-Rao lower bound (BCRLB) is utilized as the optimization criterion for the JTOPA strategy. The JTOPA is a two-variable nonconvex optimization problem. We develop a spectral projected gradient based method to solve the problem. Simulations show that the proposed JTOPA strategy effectively improves the tracking performance compared with the uniform threshold setting and power allocation in the cognitive radar network.

Joint Dwell Time and Bandwidth Optimization for Multi-Target Tracking in Radar Network Based on Low Probability of Intercept.

Radar network systems have been demonstrated to offer numerous advantages for target tracking. In this paper, a low probability of intercept (LPI)-based joint dwell time and bandwidth optimization strategy is proposed for multi-target tracking in a radar network. Since the Bayesian Cramer–Rao lower bound (BCRLB) provides a lower bound on parameter estimation, it can be utilized as the accuracy metric for target tracking. In this strategy, in order to improve the LPI performance of the radar network, the total dwell time consumption of the underlying system is minimized, while guaranteeing a predetermined tracking accuracy. There are two adaptable parameters in the optimization problem: one for dwell time, and the other for bandwidth allocation. Since the nonlinear programming-based genetic algorithm (NPGA) can solve the nonlinear problem well, we develop a method based upon NPGA to solve the resulting problem. The simulation results demonstrate that the proposed strategy has superiority over traditional algorithms, and can achieve a better LPI performance of this radar network.

JPBA of ARN for target tracking in clutter

Networked radar systems can be used to improve target tracking performance. In the asynchronous radar network (ARN) system, the radars may work at different sampling rates, bringing difficulties in resource allocation. In this study, the authors propose a joint power and bandwidth allocation (JPBA) strategy to track a target by ARN in clutter. First, they build an asynchronous resource allocation model, in which a periodic allocation strategy is suggested. Second, they derive the Bayesian Cramer–Rao lower bound by incorporating the information reduction factor as a performance metric for the JPBA strategy. Third, the asynchronous power and bandwidth allocation optimisation problem are formulated by minimising the tracking root-mean-square error with given power and bandwidth budgets, which is non-convex but monotonic. Finally, by introducing the branch-reduce-and-bound algorithm, a global solution to the optimisation problem is obtained. Numerical results verify the validity of the proposed JPBA strategy for target tracking by ARN.

Optimal Target Assignment with Seamless Handovers for Networked Radars.

This paper proposes a binary linear programming formulation for multiple target assignment of a radar network and demonstrates its applicability to obtain optimal solutions using an off-the-shelf mixed-integer linear programming solver. The goal of radar resource scheduling in this paper is to assign the maximum number of targets by handing over targets between networked radar systems to overcome physical limitations such as the detection range and simultaneous tracking capability of each radar. To achieve this, time windows are generated considering the relation between each radar and target considering incoming target information. Numerical experiments using a local-scale simulation were performed to verify the functionality of the formulation and a sensitivity analysis was conducted to identify the trend of the results with respect to several parameters. Additional experiments performed for a large-scale (battlefield) scenario confirmed that the proposed formulation is valid and applicable for hundreds of targets and corresponding radar network systems composed of five distributed radars. The performance of the scheduling solutions using the proposed formulation was better than that of the general greedy algorithm as a heuristic approach in terms of objective value as well as the number of handovers.

2.4 GHz SQUARE RING PATCH WITH RING SLOT ANTENNA FOR SELF INJECTION LOCKED RADAR

Abstract: The radar network system requires high-cost frequency, the complex configuration component of the electromagnetic feeding network circuit to make four output antenna with the same power and different phase output specifically for SIL (Self Injection Locked) Radar, and inexpensive material, especially for the electromagnetic component. 2.4 GHz Square Ring Patch with Ring Slot Microstrip Antenna with four output that has the same power using power divider and 90-degree phase different output for SIL Radar. this is the novel shaped microstrip Antenna with the free frequency, more unassuming configuration, and inexpensive material at the 2.4 GHz for SIL Radar. This system is an important part component of SIL Radar that is package consists of a 2.4 GHz Microstrip antenna with the Square Ring Patch with Ring Slot, double power divider which is double input with quad output with the same power and directional coupler 90-degree phase difference with two input and two output. The Antenna has single band and narrow bandwidth with the frequency is 2.38 GHz until 2.43 GHz under -10dB S parameter and frequency resonance 2.4 GHz, the radiation pattern is directional and the gain is 8.37 dBi, The Power divider has S parameter 2 port output of one part under -20dB at 2.4 GHz and isolation above -4dB that is all good agreement. The 90-degree hybrid coupler has S35 of -35.95dB, S46 of 35.09, S53 of -3.47, and S64 of -3.39 that all is qualified good operation. And overall size of the proposed antenna system is 100 mm times 55.7 mm with FR4 (Phenolic White Paper) with a dielectric constant is 4.4 that has 50ohm. DOI : https://doi.org/10.26905/jeemecs.v2i2.3253