Academic literature on the topic 'Radar function'

The phased array multi-function radar is an effective solution to the requirement for simultaneous surveillance and multiple target tracking. However, since it is performing the jobs usually undertaken by several dedicated radars its radar time and energy resources are limited. For this reason, and also due to the large cost of active phased array antennas, it is important for the strategies adopted in the control of the radar to be efficient. This thesis investigates and develops efficient strategies for multi-function radar control and tracking. Particularly the research has focused on the use of rotating array antennas and simultaneous multiple receive beam processing. The findings of the research challenge the traditional view that three or four fixed (static) array faces is the best antenna configuration for a multi-function radar system. By developing novel methods for the comparison of systems utilising different antenna configurations it is shown that a rotating array multi-function radar performs the surveillance function with a greater efficiency in its use of radar time than a static array system. Also, a rotating array system benefits from the ability to distribute the radar resources over the angular coverage in a way that is impossible with a static array system. A novel strategy is presented to achieve this, which allows the rotating array system to better support the realistic situation of a high concentration of radar tasks in a narrow angular sector. It is shown that the use of broadened transmit beams coupled with simultaneous multiple narrow receive beams can eliminate the compromise on radar beamwidth between the surveillance and tracking functions that is associated with multi-function radars. This technique would allow construction of multi-function radar systems with narrow beamwidths, giving improved tracking performance, without extending search frame times excessively. Efficient tracking strategies for both static array and rotating array multi-function radars are developed. They are applied through computer simulation to demonstrate tracking of highly manoeuvrable targets with a narrow beam multi-function radar. Track robustness is attained through the use of multiple beam track updating strategies at little cost in terms of radar time.

The risk of collision increases, as the number of cars on the road increases. Automotive radar is an important way to improve road traffic safety and provide driver assistance. Adaptive cruise control, parking aid, pre-crash warning etc. are some of the applications of automotive radar which are already in use in many luxury cars today. In automotive radar a commonly used modulation waveform is the linear frequency modulated continuous waveform (FMCW); the return signal contains the range and velocity information about the target related through the beat frequency equation. Existing techniques retrieve target information by applying a threshold to the Fourier power spectrum of the returned signal, to eliminate weak responses. This method has a risk of missing a target in a multi-target situation if its response falls below the threshold. It is also common to use multiple wide angle radar sensors to cover a wider angle of observation. This results in detecting a large number of targets. The ranges and velocities of targets in automotive applications create ambiguity which is heightened by the large number of responses received from wide angle set of sensors. This thesis reports a novel strategy to resolve the range-velocity ambiguity in the interpretation of FMCW radar returns that is suitable for use in automotive radar. The radar ambiguity function is used in a novel way with the beat frequency equation relating range and velocity to interpret radar responses. This strategy avoids applying a threshold to the amplitude of the Fourier spectrum of the radar return. This novel radar interpretation strategy is assessed by a simulation which demonstrates that targets can be detected and their range and velocity estimated without ambiguity using the combined information from the radar returns and existing radar ambiguity function.

Thesis (M.S. in Electrical Engineering and M.S. in Systems Engineering) Naval Postgraduate School, September 1994.<br>Thesis advisor(s): G. S. Gill. "September 1994." Includes bibliographical references. Also available online.

The multifunction radar, aided by advances in electronically steered phased array technology, is capable of supporting numerous, differing and potentially conflicting tasks. However, the full potential of the radar system is only realised through its ability to automatically manage and configure the finite resource it has available. This thesis details the novel application of agent systems to this multifunction radar resource management problem. Agent systems are computational societies where the synergy of local interactions between agents produces emergent, global desirable behaviour. In this thesis the measures and models which can be used to allocate radar resource is explored; this choice of objective function is crucial as it determines which attribute is allocated resource and consequently constitutes a description of the problem to be solved. A variety of task specific and information theoretic measures are derived and compared. It is shown that by utilising as wide a variety of measures and models as possible the radar’s multifunction capability is enhanced. An agent based radar resource manager is developed using the JADE Framework which is used to apply the sequential first price auction and continuous double auctions to the multifunction radar resource management problem. The application of the sequential first price auction leads to the development of the Sequential First Price Auction Resource Management algorithm from which numerous novel conclusions on radar resource management algorithm design are drawn. The application of the continuous double auction leads to the development of the Continuous Double Auction Parameter Selection (CDAPS) algorithm. The CDAPS algorithm improves the current state of the art by producing an improved allocation with low computational burden. The algorithm is shown to give worthwhile improvements in task performance over a conventional rule based approach for the tracking and surveillance functions as well as exhibiting graceful degradation and adaptation to a dynamic environment.

Thesis (M.S. in Electrical Engineering) Naval Postgraduate School, December 1993.<br>Thesis advisor(s): Gurnam S. Gill ; Adbel Aziz Mohamed Darwish. "December 1993." Includes bibliographical references.

Accurate rainfall forecasting using weather radar imagery has always been a crucial and predominant task in the field of meteorology [1], [2], [3] and [4]. Competitive Radial Basis Function Neural Networks (CRBFNN) [5] is one of the methods used for weather radar image based forecasting. Recently, an alternative CRBFNN based approach [6] was introduced to model the precipitation events. The difference between the techniques presented in [5] and [6] is in the approach used to model the rainfall image. Overall, it was shown that the modified CRBFNN approach [6] is more computationally efficient compared to the CRBFNN approach [5]. However, both techniques [5] and [6] share the same prediction stage. In this thesis, a different GRBFNN approach is presented for forecasting Gaussian envelope parameters. The proposed method investigates the concept of parameter dependency among Gaussian envelopes. Experimental results are also presented to illustrate the advantage of parameters prediction over the independent series prediction.

High-definition source images for those used in this document are available here: http://hdl.handle.net/10945/13822<br>Approved for public release, distribution unlimited<br>Assessment of coastal ocean conditions is valuable for both military and civilian operations. Remote sensing of those conditions can be even more valuable, particularly in the case of all-weather sensor types. The potential for better understanding of ocean conditions through the combination of remote sensing results was recognized here with the focus on SAR imagery and High Frequency (HF) radar-derived surface currents. The hypothesis that combining remote sensing products may improve results was tested using SAR imagery and available HF radar surface current maps along central California. Data were obtained from 2007-2010 when the network of HF radar stations was operating relatively continuously. Over the same time period, 780 archived SAR images were identified and, of those, 31 images were chosen for detailed assessment by identifying representative images under weak, moderate, and strong wind conditions. As expected, wind strength played a dominant role in determining the physical processes visible in the SAR imagery. Moderate wind speed of 24 m/s exhibited the most obvious ocean-related processes and the best correlation with features in the HF radar surface current maps. Surprising is the discovery that oceanographic features in the SAR imagery represent recent history of tracer advection over hours to days. As such, individual hourly, surface-current snapshots are not, perhaps, the best product for comparing with those features. Features in the daily-average currents, for example, appear more highly correlated with features in SAR imagery under moderate wind conditions.

The goal of this thesis study is to investigate the Ambiguity Function Technique for target detection in phase-coded continuous wave radar. Also, phase shift keying techniques are examined in detail. Continuous Wave (CW) Radars, which are also known as Low Probability of Intercept (LPI) radars, emit continuous signals in time which are modulated by either frequency modulation or phase modulation techniques. Modulation of the transmitted radar signal is needed to estimate both the range and the radial velocity of the detected targets. In this thesis, Phase Shift Keying (PSK) techniques such as the Barker codes, Frank codes, P1, P2, P3, P4 codes will be employed for radar signal modulation. The use of Ambiguity Function, which is a non-linear Time- Frequency Representation (TFR), for target detection will be investigated in phasecoded CW radars for different target scenarios.

Continuous Wave (CW) radars are preferred for their low probability of intercept by the other receivers. Frequency modulation techniques, the linear frequency modulation (LFM) technique in particular, are commonly used in CW radars to resolve the range and the radial velocity of the detected targets. The conventional method for target detection in a linear FMCW radar makes use of a mixer followed by a low-pass filter whose output is Fourier transformed to get the range and velocity information. In this thesis, an alternative target detection technique based on the use of the Ambiguity Function (AF) will be investigated in frequency modulated CW radars. Results of the AF-based technique and the conventional Fourier-based technique will be compared for different target detection scenarios.