We investigate three emerging topics essential for the development of cognitive radar (CR) for spectrum sharing: the response time (RT) of the CR, the autonomous regulation of the perception-action cycle (PAC), and the regulation of cognition. The RT measures the latency of all algorithms/hardware and is examined with respect to enabling capabilities of software-defined systems for rapid flexibility and responsiveness. The autonomous regulation of the PAC determines “how fast the CR can interact with the environment” as well as “how fast the CR should interact with the environment.” The regulation of the PAC is explored with respect to pulse-to-pulse waveform agility to coexist successfully with dynamic radio frequency emitters in the ambient electromagnetic environment (EME) and the consequence of modifying the waveform within the coherent processing interval. Finally, the regulation of cognition determines how to select a particular CR technique appropriately for a given dynamic environment. This selection requires a high level, or metadecision process to identify the appropriate CR technique as the EME changes over time and we therefore concentrate discussion on the newly emerging topic for radar called metacognitive radar. The exploration of these three topics include a review of past and current research with discussion of possible future research.

Power amplifiers in modern wireless systems must meet increasingly stringent spectral constraints while still operating with high power efficiency. A new peak-search algorithm is demonstrated to find the Pareto optimum of power-added efficiency (PAE) while producing an adjacent channel power ratio (ACPR) value under a specified maximum. A peak-search is first performed for the maximum PAE, and then a small-step steepest descent walk in the ACPR is taken from the PAE maximum toward the ACPR minimum until ACPR requirements are met. This approach reasonably approximates the Pareto optimum for the device. Simulation and measurement data are presented for searches from multiple starting points, and good correspondence is obtained for the Pareto optimum reflection coefficient, as well as the optimum PAE and ACPR values. This measurement-based algorithm is expected to find useful application in real-time adaptive radio and radar transmitters, as well as in bench-top measurements for amplifier design.

Adaptive radar systems will be required to operate in different frequency bands with spectrum requirements that will likely change both in time and with geographic region. A new algorithm is presented that allows direct optimisation of an amplifier's load reflection coefficient to find a Pareto optimum between the power‐added efficiency (PAE) and adjacent‐channel power ratio. Comparisons of simulation and measurement results are presented. The new algorithm's results compare well with traditionally acquired data and show consistency between the optimum values for PAE that are obtained from different starting points. Measurement comparison is performed with the previous optimisation algorithm reported by the authors, and results show that up to a 50% reduction in the number of measured experimental queries can be obtained. This translates into a significant time savings in reconfiguring a radar transmitter power amplifier.

Amplifier design, both in traditional approaches and real-time circuit optimization, greatly benefits from fast and thorough extraction of information from measurement data. Using only a few performance samples at varying impedances, deep learning image completion techniques can be utilized to extrapolate an entire set of Smith chart load-pull contours. In addition to speeding nonlinear device characterizations, this extrapolation can be performed in an iterative fashion for use as a circuit optimization algorithm with a very low number of measurements. The techniques of this work have been tested in the measurement of a nonlinear, large-signal amplifier. The load impedance can be estimated with a typical error of < 0.1 linear units using as few as seven impedances and yields even better accuracy with larger sample sizes.

Dynamic spectrum allocation will require cognitive radar transmitters to change operating frequency and bandwidth in real time. This will require high-power reconfigurable circuitry to improve radar performance by simultaneously increasing (1) the output power of the transmit waveform and (2) the power-added efficiency of the power amplifier. This circuitry is also used to mitigate co-channel interference by maintaining sufficiently linear performance so that the output waveform conforms to a given spectral mask. In this approach, a 90 W evanescent-mode cavity tuner is reconfigured using a specially designed gradient search to find the best combination of resonant cavity position numbers. This approach will be much more flexible for field use than typical Smith Chart-based load-pull searches, which require a characterization that is susceptible to drift. Experimental results are presented showing that the efficiency, output power, spectral performance, and estimated maximum radar detection range are improved significantly by re-tuning the matching network at each operating frequency. Additionally, this paper discusses innovations to reduce or eliminate time bottlenecks in a cognitive radar system for impedance tuning, reducing the time needed for complete impedance tuning searches from minutes to seconds. This significant timing reduction makes tunable power amplifiers a feasible option for future use in spectrum sharing by cognitive radar systems.

In the increasingly congested wireless spectrum, phased-array transmitters can be used to provide spatial diversity as an additional measure of coexistence. Reconfigurable matching networks placed between the power amplifier device and the antenna can allow the amplifiers in the transmitter elements to maximize output power while maintaining the desired beam fidelity. A challenge with the use of reconfigurable matching networks in array transmitters is that they alter the system calibration. This article provides measurement validation of an in situ measurement approach to assess antenna input current using a dual-directional coupler placed in an array element. Measurement validation was performed using a two-port vector network analyzer (VNA) with a load—pull tuner emulating changing antenna impedance. This approach is expected to ease the process of maintaining the pattern and is expected to ease issues stemming from changing array calibration with reconfigurable array element circuits.