Antennas are devised for the purpose of transmission and reception. In transmission, the antenna objective is to create a current/voltage distribution at the aperture surface which will create a specified beam pattern. In reception, the antenna produces an output signal whose magnitude and phase correspond to the incoming signal's magnitude and phase according to the antenna beam shape. General antenna theory provides concepts and rules for ESA analysis. Antenna analysis assumes linearity and superposition to decompose solutions into frequency and angular components.

An ESA design is a collection of sampled gain and phase states of its elements. There are numerous design techniques to achieve a desired result. In principle, any specific beam pattern has only one parametric realization. Accordingly, various design techniques striving for the same performance should generate similar designs. This section will discuss optimization of the mainbeam and sidelobes. Improving one unfortunately tends to degrade the other. Mainbeam shaping is usually a matter of obtaining the desired beamwidth. Sidelobes are rarely beneficial as they are responsible for mainbeam gain reduction, small target masking, false target insertion, and other signal artifacts. Most techniques for sidelobe reduction are applicable to both transmit and receive antenna patterns but often penalize the transmit efficiency. Since the system performance is a function of the product of the transmit and the receive antenna patterns, it is desirable to apply as much of the sidelobe mitigation as possible to the receive function.

In converting a design into hardware, there is seldom an exact match between as-designed and as-built, so performance will deviate from prediction. System requirements must be decomposed into subsystem specifications and tolerances compared with accuracy achievable with available components. Design and simulation with software tools utilize parameters that are exact to many decimal places. An essential step in the design process is to assess the sensitivity of predicted performance to inaccuracies, including temporal changes. This chapter describes common error sources and assesses their effects. The effect of errors is to degrade antenna performance metrics that include beam pointing, beamwidth, sidelobe magnitude, and location. Correlated errors such as phase and gain quantization tend to be more noticeable but their average effect is comparable to random errors. Errors may arise from component or fabrication variation or from partial or complete component failure. Intentional deactivation of elements, may also be analyzed as a failure whose effects vary. For instance, turning off one-half of the array has greatly different effects depending on whether those elements are on one side of the array, alternate rows or columns of the array, or randomly selected. It is necessary to assess the specific design options to determine the importance of these errors.

The analysis in this book primarily concerns conventional arrays with elements spaced uniformly across a specified aperture to achieve specified performance: radiated power, sidelobes, etc. In this chapter, we consider thinned (or sparse) arrays by which we mean conventional arrays from which some number of elements have been deliberately removed. Rocca et al. provide an overview of types of irregular arrays and associated design techniques. Thinned arrays are useful in cases where the design complies with most performance requirements while exceeding others. It may be possible to reduce the excess performance (and cost) by selectively removing some elements.

The techniques described in the previous chapter dealt primarily with sidelobes without constraining the resulting mainbeam width and shape. It is sometimes desirable to form a broad beam, of constant or shaped amplitude. Examples include fan beams for increasing SAR swath coverage or cosecant beams for air surveillance where range varies with elevation angle. This chapter discusses the last three techniques.

Designs are never ideal, and compromises are necessary to reconcile requirements with size, weight, power, and cost. ESA antennas provide unique benefits to improve performance which must be weighed against their greater cost and complexity The first consideration in the design process is to devise an architecture consistent with system constraints and capable of satisfying system requirements. This requires a functional decomposition and partition, bearing in mind practical considerations such as component cost and availability. It is typically an iterative process, as each design iteration reveals opportunities for improvement and difficulties in realization.

T/R modules are the heart of an ESA and their continued improvement has been the key to ESA development. T/R modules provide distributed gain and phase control, typically at each radiating element. They provide flexibility enabling the attractive performance of the ESA. There are many good examples in systems and many more concepts described in the literature. The cost of T/R modules has been the most important restriction on their wide use. Since the 1990s, costs have declined precipitously, leading to the vast increase in ESA applications, primarily because of commercial demand for MMICs, application-specific integrated circuits (ASICs), and other components.

Cost is a dominant consideration with ESAs and was historically the principal reason that ESAs were not more prevalent. Cost represents a significant competitive discriminator, so this information is rarely published. Accordingly, the cost discussion in this chapter is necessarily inferential. Large investments in R&D have mitigated most of these issues to the point that ESAs are cost competitive with other antenna types, particularly in view of their additional capabilities difficult or impossible to achieve with traditional designs. Historically, T/R modules constituted about 50% of the cost of an ESA and components were about 50% of the cost of the T/R module. Accordingly, considerable effort was expended on both component and module cost. These estimates were predicated on high reliability (military) requirements and standards. Commercial systems relaxe these constraints with commensurate cost savings. Cost is a strong function of both production rates and quantities. In 2001, a US Defense Science Board Study titled Future DoD Airborne High-Frequency Radar Needs/Resources [1] forecast a requirement for a total of 6 million T/R modules for current and planned US military programs through 2021. Ultimately, the demand for ESAs was sufficient to support dedicated production lines, using similar components, processes, and equipment as their commercial counterparts and achieving commensurate cost savings.

There does not appear to be a conclusive advantage for ESA or ESA-fed reflectors for the earth observation mission. At X-band, ESAs seem to be the dominant choice, in part because the antennas are smaller and also because of the huge technology base developed for airborne and ground-based radars. At lower frequencies, the reflector benefits are more compelling as the antennas are larger. In many cases, the experience base at the manufacturer will determine the outcome for cost and risk benefits. Relative merits will continue to evolve.

MATLAB® scripts were used to create most of the figures in this book and for the associated short course. The name of the script is shown beneath its associated figure. The programs are available for download from the publisher's website at https://digital-library.theiet.org/. The scripts do not include a user interface or extensive error checking. Parameters are hard-coded but may be altered to assess other cases. The underlying engineering formulae represent relatively few lines of the program; much of the rest relates to graphical output and format. The program run times range from seconds to hours. Run times depend, in large part, on the size of arrays and the number of iterations (cases).