The evolution of radar proceeded in a number of steps, of which each had a fundamental effect on the performance. In the beginning, the radar was built using all- analogue technology with an analogue display. Information extraction was performed at that time by adjusting the dynamic range of the cathode-ray display. A big improvement was obtained when the output data after analogue filtering and signal processing were sampled and digitized. This allowed some post processing of these data. A number of detection techniques with different algorithms and adaptive thresholds could be implemented. The algorithms could be changed by software if necessary. Digital displays provided a clear extraction of the relevant information.
With the increasing availability of fast analogue-to-digital converters and computers, the point of digitization could then be shifted more and more towards the antenna such that programmable filters and signal processing algorithms could be applied. This allowed to apply all the flexibility of digital signal processing in the time domain.
In parallel, a major step was achieved by sampling and digitizing data in the spatial domain as well. This started the era of antenna-array processing. Even if certain reduced forms of spatial samples are digitally available, this concept may offer new options: digital beamforming with different weightings and pattern shap- ing, adaptive beamforming, mismatched spatial filtering, multi-target filtering and super-resolution. These are the concepts that are considered in Part I of this book
‘Real Aperture Array Radar’. The efficiency of these real-aperture-array-processing methods depends strongly on the kind of spatial sampling. We may have fully filled arrays, sparse arrays, arrays with partial digital beamforming using sub-arrays and linear, planar or volume arrays. Therefore, the array configuration has to be con- sidered in combination with the spatial processing algorithms. Furthermore, the processing methods in time and space have an implication on the resulting parameter estimates as well as on the target detection performance. Therefore, the array con- figuration and the aspects of detection and estimation have to be considered jointly.
With digital signal processing, different methods resulting from different optimality criteria can be applied for each radar application, and it is possible to switch rapidly between different applications or radar modes. This is the concept of multi-function radar, which is a key application of real aperture array radar.
1Fraunhofer FKIE, Germany
The third jump in radar technology was by overriding the fixed spatial sampling scheme given by the mechanical setup, and this was achieved by spatial sampling sequentially in time in a defined sequence. This opens a great flexibility and leads to the big field of synthetic aperture radar (SAR) and inverse SAR. Applying these principles also on transmit signals opens the field of multiple-input–multiple-output radar. The theory of compressive sensing provides the theoretical background of proper and efficient sampling and processing of such 2D data fields. All these novel radar techniques will be considered in Parts II and III of this book. Actually, most techniques for real aperture array radar will also be applied in a modified form for the novel techniques, too. In this sense, the first part of this book provides the basis for the subsequent parts.
The task of modern radar is not to simply detect a target. The radar should provide relevant information of all features of interest of a target, where it depends on the specific application what the relevant information is. This requires the development of a mathematical model of the target and then to estimate the feature parameters of this model. The target dynamic behaviour is of particular interest, but other features like the radar cross-section, micro-Doppler fluctuation may be of interest too, e.g. for classification. Estimation of the dynamic target parameters is the topic of target tracking which is considered in Part II in Volume 2 of this book.
Modern Bayesian tracking algorithms offer the possibility to exploit all kinds of information about the target and the environment. For optimum performance, all this information should be exploited. Such information can be gained by learning with the radar itself, or from other additional sensors or radars. Thus, we are led to netted radar systems and multiple sensor systems for which one has to apply intelligent sensor-data-fusion techniques, which is a topic of Part II in Volume 2 of this book.
A radar system with digital processing is able to switch between different modes of operation. A system that exploits adaptively all information about the target and the environment and which controls the radar operational modes adap- tively according to this information has been termed ‘cognitive radar’ [1]. This feature is in fact the objective of a ‘novel-radar’ system to be considered in this book. It comprises the tasks of information extraction from different sensors and from big data bases, information processing and sensor-fusion techniques and adaptive control of all involved sensors. There is no cookbook on cognitive radar, but this present book can provide various aspects of such a system. The critical feature of a cognitive radar is that various constraints have to be fulfilled resulting from the hardware, the platform or the environment. In reality, the constraining requirements are often contradicting. The art-of-radar-system engineering consists of handling these constraints by matching the different hardware and software components of the system to fulfil the requirements in a good compromise. The antenna, signal processing, data processing, operational modes, resources and time management must be carefully designed in this sense.
What has all this to do with real aperture array radar? In fact, the real aperture radar already includes many aspects of novel, cognitive radar in a nutshell. It is the objective of the first part of this book to give an introduction to these problems for the more simple case of a real aperture.
Chapter 1 is quite comprehensive, and it serves to provide the relevant knowledge about array radar. It does not contain too much detail but covers the basic knowledge and interrelations between the processing blocks. The objective is to give a unified view of the related problems rather than introducing the latest novel algorithms. The issues of interest are the generic algorithms, the relations to the antenna design, the influence of hardware components, an analysis of the parameter estimation and detection problem, the relations to target tracking, the special features of applications and system operational modes and system control.
Much emphasis is laid on the aspects of adaptive processing. For this case, parti- cular relationships to the antenna configuration and the hardware features are evaluated and the detection and tracking procedures are reviewed. From a system design viewpoint, a key requirement of any adaptive processing is a well-defined behaviour and system predictability.
Chapter 2 considers combined space-time adaptive processing (STAP) for air- borne radar application. Usually, adaptation is based on a second independent-training data set and on the assumption that the interference scenario is stationary over the processing time. In this section, an alternative interference cancellation technique is presented with minimal training data taken from the same range cell. Such ‘single- snapshot’ or ‘direct-data-domain’ techniques can overcome the problems of statio- narity and limited sample support of standard adaptive processing, but they are also prone to deficiencies like target self-nulling. Direct data domain STAP is thus a good example of finding an improved solution satisfying different contradicting constraints.
This is again a case where the simple real-aperture-array radar can provide examples of novel approaches that may be applicable to the more complicated techniques in Parts II and III in Volume 1 and Parts I and II in Volume 2.
Chapter 3 provides the state-of-the-art of multi-function radar and of the management of the radar operational modes. Multiple-mode operation is today the most attractive feature of real aperture array radar. The management of all possible modes, full exploitation of the hardware resources, efficient use of the data and communication resources is a problem of high complexity. At this time, we are just at the beginning of understanding and exploiting all the possibilities in this area.
Consequently, this topic will be revisited and extended in some sections of Parts I and II of Volume 2.
With the mixture of relevant topics in the five parts of this book, I am confident that this book will give a valuable contribution to the radar community. If this book will eventually become a success, this will be to a great deal due to my colleague Richard Klemm who had the idea of compiling this kind of book and who managed the editorial process together with the excellent support of the IET publishing department.
Reference
[1] S. Haykin: Cognitive Radar, IEEE Signal Processing Magazine, January 2006, pp. 30–40.