In this chapter we discuss design techniques and constraints that facilitate a waveform that is useful for radar. While signal-to-noise ratio (SNR) and signal-to-interference-plus-noise ratio (SINR) have historically been the primary drivers of waveform design and are certainly discussed here, the growing need for spectral coexistence is eliciting new metrics and design approaches that address a broader set of considerations. This chapter also examines the use of performance prediction models as a means to establish relationships between waveform constraints and SINR performance, which are critical for detection in spectrally crowded environments. An empirical approach is discussed along with models that provide an intuitive way to understand the complex relationships between constraints and SINR performance in dynamic situations.

Chapter Contents:

• 17.1 Introduction
• 17.1.1 Waveform design for interference mitigation
• 17.1.2 The role of practical constraints
• 17.1.3 Performance prediction (empirical vs. analytic)
• 17.2 Representing interference and noise for waveform design algorithm development
• 17.2.1 Auto-regressive parametric models
• 17.2.2 Marenko–Pastur generalized model
• 17.2.3 Empirical models
• 17.3 Modelling SINR loss for spectral coexistence (radar centric)
• 17.3.1 Cumulative modulus
• 17.3.1.1 Numerical results
• 17.3.1.2 Application to waveform design
• 17.3.2 Integrated sidelobe constraints
• 17.3.2.1 Expected ISL performance model
• 17.3.2.2 Expected SINR performance model
• 17.3.3 Simulation results and comparison to measured data
• 17.4 Alternative metrics for spectrally crowded engagements
• 17.4.1 Maximizing information
• 17.4.2 Mutual information for cognitive radar
• 17.4.3 Example with primary users
• 17.5 Summary
• 17.6 Looking ahead
• References

Inspec keywords: spectral analysis; radar signal processing; prediction theory

Other keywords: radar waveform design; spectral coexistence; primary drivers; design techniques; signal-to-noise ratio; spectrally crowded environments; SINR performance; SNR; signal-to-interference-plus-noise ratio; performance prediction models

Subjects: Radar theory; Signal processing and detection