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.

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.

With many frequency bands previously allocated solely for radar now being reallocated for sharing, radar transmitters must be frequency-agile, able to quickly change operating frequency while maintaining detection range. This article details the design of a 2–4-GHz reconfigurable impedance tuner using 35-W plasma switches. The tuner consists of switched shunt capacitor and inductor branches loading a series microstrip line. For many RF matching applications, a reconfigurable impedance tuner must have a broad tuning bandwidth, real-time switching speeds, high power handling, low loss, and broad Smith chart coverage. The implementation of the tuner using semiconductor plasma switches illuminated by laser diodes is described. The tuner is demonstrated in measurements using a custom search algorithm, adjusting and optimizing the tuner settings to provide maximum output power in approximately 300 $\mu$ s upon changes in operating frequency or antenna impedance. This tuner provides superior reconfiguration times over other high-power tuners in the literature. The tuner possesses losses as low as 0.77 dB and at least 30% Smith chart coverage over the entire tunable bandwidth. With a 26.7- $\mu $ s switching speed, the impedance tuner is also demonstrated to handle 20 W of power at all frequencies and states with over 40 W of power for greater than half of the octave bandwidth and power handling measured as high as 70 W. The combination of fast reconfiguration and high power handling in an impedance tuner can enable cognitive radar systems to adapt to a congested and dynamic environment in real time.

Future radar transmitters must be adaptive and reconfigurable in real time to be able to share spectrum dynamically with wireless communications. We demonstrate the joint, back-and-forth optimization of the radar transmitter waveform and circuitry in a combined algorithm that can be used for real-time reconfiguration. While previously developed methods consider the waveform and circuit separately, resulting in emphasis on one of the criteria (ambiguity function or power efficiency) we show that the joint optimization of the circuit and waveform allows both the radar ambiguity function and circuit power-added efficiency criteria to be gradually improved during the optimization. Measurement results are presented and analyzed to assess the convergence of the power-added efficiency and ambiguity- function least-squares error, as compared to the ambiguity function template during an optimization under spectral mask and peak-to-average power ratio constraints.