The digital signal processing algorithms employed in radar and sonar applications invariably involve the manipulation of time series samples taken from a multiplicity of sensor elements. Matrix algebra provides a powe...
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The digital signal processing algorithms employed in radar and sonar applications invariably involve the manipulation of time series samples taken from a multiplicity of sensor elements. Matrix algebra provides a powerful symbology to represent such samples and to analyze their manipulation in a concise manner. Once candidate algorithms have been expressed in this algebra there are a wealth of techniques and theorems available to assist with the prediction of performance, and thereby optimise the design of the finally implemented signal processing structure. The author reviews the use of matrix algebra to represent sample signals and to analyze digital signal processing algorithms. He also presents some of the key theorems of matrix algebra that find applications in such analysis.< >
Examines the differences and similarities between the requirements and execution of digital signal processing in radar and sonar systems. The major differences are caused by the 2*10/sup 5/ ratio in the velocities of ...
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Examines the differences and similarities between the requirements and execution of digital signal processing in radar and sonar systems. The major differences are caused by the 2*10/sup 5/ ratio in the velocities of propagation of electromagnetics and sound. This results in differences in the bandwidths of the signals employed, the durations of the time windows that can be processed, differences in the ways that Doppler shifts are processed and the urgent need in sonar for the use of beam steering using electronic methods. The wavelengths involved in radar and sonar overlap. At HF radars also need to employ electronic methods to steer beams. The time-bandwidth products involved in radar and sonar are also very similar. The paper also reviews the basic methods of processing in the time, frequency and spatial domains. Spectrum analysis is often the key to the algorithms used.< >
For pt.I see ibid., p.411 (1990). Outlines techniques that have been developed for high performance complex vector processing operations, in particular methods to implement efficient discrete Fourier transforms, and i...
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For pt.I see ibid., p.411 (1990). Outlines techniques that have been developed for high performance complex vector processing operations, in particular methods to implement efficient discrete Fourier transforms, and introduces some techniques, based on graph theory, for partitioning flow graphs with application to target tracking and system partitioning for distributed network CAE/CAD.< >
The use of synthetic aperture radar (SAR) techniques is becoming increasingly widespread in a number of applications ranging from satellite remote sensing of land and sea, through to target imaging from airborne radar...
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The use of synthetic aperture radar (SAR) techniques is becoming increasingly widespread in a number of applications ranging from satellite remote sensing of land and sea, through to target imaging from airborne radars for military purposes. The signal processing associated with high quality SAR imaging can be very complex. In addition, very large quantities of data often require to be processes and in many cases real time operation is also necessary. An introduction is provided to the fundamental principles of SAR and inverse synthetic aperture radar (ISAR), so that the requirements of suitable digital signal processors can be better understood.< >
Covers some of the fundamental features of radar signal processing. Some of the properties of radar signals are examined; since these define some of the main problems which the radar designer faces as he or she attemp...
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Covers some of the fundamental features of radar signal processing. Some of the properties of radar signals are examined; since these define some of the main problems which the radar designer faces as he or she attempts to design a radar and associated signal processor. An important aspect of radar is that of waveform design, and understanding the properties and limitations of the waveforms that are used. These waveform properties directly affect the performance of the radar in detection performance and measurement accuracy. The techniques and algorithms that are used in current radar systems are briefly reviewed, highlighting some of those which are likely to be improved by the recent improvements in signal processing technology.< >
Summarises the essential theory using a coherent and up-to-date form of presentation based entirely on orthogonal rotations. The application of orthogonal rotations to adaptive beamforming is now well established but ...
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Summarises the essential theory using a coherent and up-to-date form of presentation based entirely on orthogonal rotations. The application of orthogonal rotations to adaptive beamforming is now well established but only very recently has the important class of least squares lattice algorithms been derived in this way. As a result of this development, the author has been able to present all of the least squares algorithms discussed in the form of processing architectures which use the same basic rotation cells. This not only provides a modern perspective but also allows the detailed mathematics to be reduced to a minimum whilst providing a complete specification of the associated algorithms.< >
Several orders of magnitude increase in computing power are required to maintain a long range surveillance capability into the 1990s and, within the next decade, typical applications will need throughputs approaching ...
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Several orders of magnitude increase in computing power are required to maintain a long range surveillance capability into the 1990s and, within the next decade, typical applications will need throughputs approaching 1000000 MIPs, significantly greater than that currently achieved with fifth generation computers. Increases of this order require simultaneous advances in several areas that impact on sonar, namely in DSP algorithm understanding, distributed system architectures and enabling technologies. The paper outlines some current work in these areas and describes front-end DSP algorithms developed for 'processing engines' realisations for use in multi-channel, high throughput sonar processing systems that can sustain this level of performance.< >
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