Ji-Eun Roh

Integrated Simulator of Airborne Multi-function Radar Resource Manager and Environment Model

In this paper, an integrated radar resource manager for an airborne multi-function radar and a radar-environment simulator are presented. The radar-environment simulator includes target detection/measurement models, a nonlinear tracking filter for the airborne radar and an effective target generation algorithm. The structures and functions of modules in the radar resource manager are established and validated by the radar-environment simulator.

Markov chain of active tracking in a radar system and its application to quantitative analysis on track formation range

Markov chains for active tracking which assigns additional track illuminations evenly between search illuminations for a radar system are presented in this article. And some quantitative analyses on track formation range are discussed by using them. Compared with track-while-search (TWS) tracking that uses scan-to-scan correlation at search illuminations for tracking of a target, active tracking has shown the maximum improvement in track formation range of about 27.6%. It is also shown that the number and detection probability of additional track beams have impact on the track formation range. For the consideration of radar resource management at the preliminary radar system design stage, the presented analysis method can be used easily without the need of Monte Carlo simulation.

Comparison on Track Formation Range between TWS and Adaptive Tracking Using Markov Chain Analysis in a Radar System

Compared with the TWS(Track While Scan) tracking that uses scan-to-scan correlation at search illuminations for targets track, a phased array radar can use adaptive tracking which assigns additional track illuminations and the track formation range can be improved as a result. In this paper, an adaptive tracking, the search and track illuminations of a target are synchronized such that the extra illuminations are evenly distributed between the search illuminations, is proposed. Markov chain and track formation range for the proposed adaptive tracking are shown with them for the conventional TWS. The simulation result shows that the proposed adaptive tracking has improved track formation range by 27.6 % compared with the conventional TWS tracking under same track confirmation criterion.

A Study on Beam Operation of an Airborne AESA Radar with Uniform Search Performance in Whole Scan Area

An Active Electronically Scanned Array(AESA) radar required necessarily as the Fire Control Radar(FCR) of recent fighters has ununiform detection range with regard to scan angle due to scan loss. Although the compensation method of scan loss in an AESA radar with variable dwell time is investigated, the effectiveness of the method in a fighter FCR with multi-function such as search, track, and missile guidance within limited resources should be considered systematically. In this paper, uniform search performance of an AESA radar using variable dwell time with regard to scan angle is derived. We assumed the search load of 50 % for case without changing dwell time in fixed frame time and showed the fighter FCR requirement for multi-function is not satisfied because the search load for the uniform search performance should be increased by about 100 %. On the other hand, in case of increasing the frame time for the uniform search performance and search load of 50 %, degradation of the search performance is shown by 86.7 % compared with the former. Based on these analyses, the effective beam operation strategy on an airborne AESA radar with uniform search performance in whole scan area is described with consideration of frame time, search load and performance as a whole.

Beam Scheduling Algorithm of Multi-Function AESA Radar Based on Dispatching Rules

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability, compared with mechanically scanned array radar. AESA radar brings a new challenges, radar resource management(RRM), which is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed the several dispatching rules for radar beam scheduling, and compared the performance on the multi-function radar scenario. We also showed that the dispatching rule which differently applying SPF(Shortest Processing time First) and ERF(Earliest Request time First) according to beam processing latency is the most efficient.

Stochastic Radar Beam Scheduling Using Simulated Annealing

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability, compared with mechanically scanned array radar. AESA radar brings a new challenges, radar resource management(RRM), which is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed stochastic radar beam scheduling algorithm using simulated annealing(SA), and evaluated the performance on the multi-function radar scenario. As a result, we showed that our proposed algorithm is superior to previous dispatching rule based scheduling algorithm from the viewpoint of beam processing latency and the number of scheduled beams, with real time capability.

Differential Choice of Radar Beam Scheduling Algorithm According to Radar Load Status

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability. For this reason, Radar Resource Management(RRM) becomes new challenging issue. RRM is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed a rule-based scheduling algorithm and Simulated Annealing(SA) based scheduling algorithm, which are alternatively selected and applied to beam scheduler according radar load status in real-time. The performance of the proposed algorithm was evaluated on the multi-function radar scenario. As a result, we showed that our proposed algorithm can process a lot of beams at the right time with real time capability, compared with applying only rule-based scheduling algorithm. Additionally, we showed that the proposed algorithm can save scheduling time remarkably, compared with applying only SA-based scheduling algorithm.

Radar Return Signal Simulation Equipment Using MC-DDS (Multi-Channel Direct Digital Synthesis)

Radar receiving echo signal provides target information - range, velocity and position by signal magnitude and Doppler shift, which are determined by target reflection characteristics and target maneuver. Target angle error is extracted from the magnitude ratio of difference channel to sum channel. In this paper, we introduce a radar Return Signal Simulation Equipment(RSSE) which is implemented for the purpose of performance analysis and evaluation of phased array multi-function radar(MFR). It generates multi-target environment with jamming signals using MC-DDS (Multi-Channel Direct Digital Synthesis), and has scalability by using the efficient hardware configuration. The performance of the developed RSSE has been evaluated under various test environments. Especially, we proved that required target detection performance is achieved by RSP(Radar Signal Processor) interfaced RSSE configuration.

Development of 3-D Multi-Function Radar High-Speed Real-Time Signal Processor

A 3-D multi-function radar(MFR) is a modern radar to provide various target information, such as range, doppler, and angle by performing surveillance, multiple target tracking, and missile guidance. In this paper, we introduced a real-time radar signal processor(RSP), which is a crucial component of MFR with its design, implementation using high-speed multiple DSP, and performance. Additionally, we verified that several advanced signal processing algorithms were well-performed in our RSP, such as MCA-CFAR algorithm for target detection in clutter environment, range and velocity measurement algorithm using discriminator estimation, and noise jammer detection algorithm using local minimum selection.

Effective Elimination of False Alarms by Variable Section Size in CFAR Algorithm

Generally, because received signals from radar are very bulky, the data are divided into manageable size called section, and sections are distributed into several digital signal processors. And then, target detection algorithms are applied simultaneously in each processor. CFAR(Constant False Alarm Rate) algorithm, which is the most popular target detection algorithm, can estimate accurate threshold values to determine which signals are targets or noises within center-cut of section allocated to each processor. However, its estimation precision is diminished in section edge data because of insufficient surrounding data to be referred. Especially this edge problem of CFAR is too serious if we have many sections to be processed, because it causes many false alarms in most every section edges. This paper describes false alarm issues on MCA(Minimum Cell Average)-CFAR, and proposes a false alarm elimination method by changing section size alternatively. Real received data from multi-function radar were used to evaluate a proposed method, and we show that our method drastically decreases false alarms without missing real targets, and improves detection performance.