Machine learning network trained to tune settings and optimize images. In accordance with one aspect, a method is provided for image optimization with a medical ultrasound scanner. A medical ultrasound scanner images a patient using first settings. A first image from the imaging using the first settings and patient information for the patient are input to a machine-learned network. The machine-learned network outputs second settings in response to the inputting of the first image and the patient information. The medical ultrasound scanner re-images the patient using the second settings. A second image from the re-imaging is displayed.

Machine learning network trained to tune settings and optimize images. In accordance with one aspect, a method is provided for image optimization with a medical ultrasound scanner. A medical ultrasound scanner images a patient using first settings. A first image from the imaging using the first settings and patient information for the patient are input to a machine-learned network. The machine-learned network outputs second settings in response to the inputting of the first image and the patient information. The medical ultrasound scanner re-images the patient using the second settings. A second image from the re-imaging is displayed.

A method is provided for estimating a velocity of an object located in the environment of a vehicle. Detections of a range, an azimuth angle and a range rate of the object are acquired for at least two different points in time via a sensor. A cost function is generated which depends on a first source and a second source. The first source is based on a range rate velocity profile which depends on the range rate and the azimuth angle, and the first source depends on an estimated accuracy for the first source. The second source is based on a position difference which depends on the range and the azimuth angle for the at least two different points in time, and the second source depends on an estimated accuracy for the second source. By minimizing the cost function, a velocity estimate is determined for the object.

A method is provided for estimating a velocity of an object located in the environment of a vehicle. Detections of a range, an azimuth angle and a range rate of the object are acquired for at least two different points in time via a sensor. A cost function is generated which depends on a first source and a second source. The first source is based on a range rate velocity profile which depends on the range rate and the azimuth angle, and the first source depends on an estimated accuracy for the first source. The second source is based on a position difference which depends on the range and the azimuth angle for the at least two different points in time, and the second source depends on an estimated accuracy for the second source. By minimizing the cost function, a velocity estimate is determined for the object.

Provided is a method and system for measuring a radar cross section of an object (102). The method comprises: transmitting one or more radar pulses (402) to the object (102), each of the one or more pulses (402) having a predetermined pulse profile; for each of the one or more pulses (402), measuring a pulse return, the pulse return being the radar pulse (402) reflected by the object (102); deconvolving the measured one or more pulse returns using the predetermined pulse profile; and determining the radar cross section of the object (102) using the deconvolved one or more pulse returns.

Low-power vehicle sentinel systems and methods are disclosed herein. An example method includes obtaining electromagnetic signals in a target area surrounding a vehicle. The electromagnetic signals can be obtained from electromagnetic elements mounted to the vehicle. The method can include determining attributes or behaviors of an object in the target area based on the electromagnetic signals and executing a response measure based on the attributes or behaviors of the object.

A method for determining a kinematic structure of a two-dimensional wind field and a system determining the same are provided. The method comprises receiving a plurality of Doppler velocities and a plurality of distances between a Doppler radar and a gate. Each Doppler velocity of the plurality of Doppler velocities corresponds to a respective distance of the plurality of distances between the Doppler radar and the gate. The method further comprises calculating a plurality of distance Doppler velocity values. The distance Doppler velocity values represent the plurality of measured Doppler velocities and the distance between the Doppler radar and the gate. The method further comprises estimating the kinematic structure of the 2D wind field using the plurality of distance Doppler wind velocity values.

A method for determining a kinematic structure of a two-dimensional wind field and a system determining the same are provided. The method comprises receiving a plurality of Doppler velocities and a plurality of distances between a Doppler radar and a gate. Each Doppler velocity of the plurality of Doppler velocities corresponds to a respective distance of the plurality of distances between the Doppler radar and the gate. The method further comprises calculating a plurality of distance Doppler velocity values. The distance Doppler velocity values represent the plurality of measured Doppler velocities and the distance between the Doppler radar and the gate. The method further comprises estimating the kinematic structure of the 2D wind field using the plurality of distance Doppler wind velocity values.

Systems and methods for using velocity measurements to adjust Doppler filter bandwidth are provided herein. In certain embodiments, a method for adjusting bandwidth for at least one Doppler filter in a Doppler beam sharpened radar altimeter comprises receiving a velocity measurement; adjusting the bandwidth of the at least one Doppler filter based on the velocity measurement; and transmitting a radar beam, wherein the radar beam is aimed toward a surface. The method further comprises receiving at least one reflected signal, wherein the at least one reflected signal is a reflection of the radar beam being reflected off of at least one portion of the surface; and filtering the at least one reflected signal with the at least one Doppler filter to form at least one Doppler beam.

Systems and methods for using velocity measurements to adjust Doppler filter bandwidth are provided herein. In certain embodiments, a method for adjusting bandwidth for at least one Doppler filter in a Doppler beam sharpened radar altimeter comprises receiving a velocity measurement; adjusting the bandwidth of the at least one Doppler filter based on the velocity measurement; and transmitting a radar beam, wherein the radar beam is aimed toward a surface. The method further comprises receiving at least one reflected signal, wherein the at least one reflected signal is a reflection of the radar beam being reflected off of at least one portion of the surface; and filtering the at least one reflected signal with the at least one Doppler filter to form at least one Doppler beam.