In the first installment of our healthcare technology series, we discussed areas where health outcomes are improving as technology shifts closer to patients. Here, we’ll scratch the surface on three trends that are improving medical imaging technologies, and by extension, diagnostics, patient outcomes and access to care. We’ll usemagnetic resonance imaging (MRI), which leverages radio frequency (RF) signals, to contextualize these trends. 

This is the third installment in our RF Components for Radar series. In the first installment, we provided an overview of the key functional units in radar, including duplexing, filtering, power amplification, waveform generation, low-noise amplification (LNA), receiving and analog-to-digital conversion (ADC). Here, we’ll focus on a particular form of filtering technology: switch filter banks. 

At Knowles, it is our mission to provide specialty components that meet even the toughest performance and reliability requirements, especially for applications where failure is not an option. But, markets and requirements are constantly changing, which means we must closely monitor the trends impacting all the industries and applications where you might find our components. One area where we are seeing rapid innovation spanning the industries we serve is power electronics. At a high level, the trends driving power electronics innovation are largely centered around methods for providing more energy more efficiently while using smaller components. Below are four key power electronics trends we are currently monitoring and a how we can help you stay on top of each trend with your designs.  

This is the second installment in our RF Components for Radar series. In the first installment, we provided an overview of the key functional units in radar, including duplexing, filtering, power amplification, waveform generation, low-noise amplification (LNA), receiving and analog-to-digital conversion (ADC). Here, we’ll focus on duplexing.  

Radar systems are designed to detect and identify an object’s location. They use short bursts of energy to transmit radio frequency (RF) and microwave signals and gather information from the echoed signal returned by the object.  

Here, we’ll introduce radar, including its key functional units and technological evolution. 

With the rising prevalence of cardiovascular, orthopedic, and other chronic conditions, and an increase in the number of patients needing care, the demand for implantable medical devices continues to increase. 

Quality factor, or Q factor, is a common shorthand figure of merit (FOM) for RF filters. It’s typically expressed as the ratio of stored versus lost energy per oscillation cycle. Steepness of skirts, selectivity, and insertion loss are all specifications that can be described in terms of Q factor. While this FOM feels ubiquitous in RF, truly understanding how Q factor is determined and how it relates to other specifications is a complex endeavor because it’s contextual. 

There are hundreds of filter applications operating across a wide range of frequencies, which presents a challenge for filter designers since most filter designs don't inherently operate across these wide ranges. Size, weight, power, and cost (SWaP-C) are also important considerations, so simply adding more filters to address different frequency ranges is not an attractive solution. There is, however, an alternative way of designing filters: combining filter technologies to meet the specific frequency, bandwidth, and size requirements of your application.

Passive gain equalizers are designed to rectify or flatten the frequency response of an RF amplifier. RF amplifiers are known to cause a non-uniform gain over the operational bandwidth of a device, which results in distortion and other unwanted effects. Equalizers generate a counter-gain profile to offset that uneven response. Pairing equalizers and amplifiers is critical in applications like broadband systems where consistent performance over a wide frequency range enhances signal fidelity and system performance.

Bias filter networks and self-bias networks are two types of biasing components developed by Knowles Precision Devices for use in high-frequency microwave and RF applications.