Abstract: A method begins by one or more processing modules of one or more computing devices of a radar system determining whether a radar signature varies cyclically with time, and when the radar signature varies cyclically with time the method continues with the one or more processing modules collecting state telemetry information for the radar signature, along with a signal representation for the radar system. The state telemetry information includes rotation angle, yaw angle and rotation rate for the object responsible for the observed radar signature and the signal representation for the radar system includes data sufficient to determine an I/Q signal for the radar system. The method then determines a characterized radar signature for the object responsible for the radar signature and based on the state telemetry and the signal representation, substantially removes the radar signature from radar data.

Abstract: A method begins by one or more processing modules of one or more computing devices of a radar system determining whether a radar signature varies cyclically with time, and when the radar signature varies cyclically with time the method continues with the one or more processing modules collecting state telemetry information for the radar signature, along with a signal representation for the radar system. The state telemetry information includes rotation angle, yaw angle and rotation rate for the object responsible for the observed radar signature and the signal representation for the radar system includes data sufficient to determine an I/Q signal for the radar system. The method then determines a characterized radar signature for the object responsible for the radar signature and based on the state telemetry and the signal representation, substantially removes the radar signature from radar data.

Abstract: Embodiments of the invention are directed toward attenuation correction of radar data. Atmospheric attenuation is a function of atmospheric water drop size and temperature. A number of different theoretical models are available to mathematically describe the particle drop shape that influences attenuation estimation. Each of these models has proven effective in different scenarios. It can be difficult, however, to predict which theoretical model to use. The total differential phase gives an idea of the attenuation, but it depends on the model. Moreover, the total attenuation along a rain path must be apportioned to different parts of the radar path in order to correct for attenuation along a radar path. Embodiments of this invention allows for a system to apportion the attenuation to different parts of the radar beam. Embodiments of the invention also allow for optimization of a number of different theoretical models for both drop size and temperature.

Abstract: Embodiments of the invention can predict the ground location and intensity of storm cells for a future time using radar reflectivity data. In some embodiments, a Sinc approximation of the general flow equation can be solved to predict the ground location and intensity of a storm cell. In some embodiments, to solve the Sinc approximation the velocity of a storm cell can be estimated using various techniques including solving the flow equation in the frequency domain. The results can provide efficient prediction of storm cell position in nowcasting applications.

Abstract: Embodiments of the invention are directed to improving the sensitivity in polarimetric radar data. In particular, embodiments of the invention improve the sensitivity of such systems with improved post processing techniques. The sensitivity can be improved by using the co-polar elements (off diagonal elements) of the covariance matrix in power and/or reflectivity determinations. This can not only improve the sensitivity but may also enhance identification and improve quantitative estimates of precipitation.

Abstract: Embodiments of the present invention provide for improved estimation of environmental parameters in a dual-polarization radar system. In some embodiments, environmental parameters can be estimated using a linear combination of data received in two orthogonal polarization states. In particular, embodiments of the invention improve ground clutter and noise mitigation in dual polarization radar systems. Moreover, embodiments of the invention also provide for systems to determine the differential reflectivity and/or the magnitude of the co-polar correlation coefficient and the differential phase in a dual polarization radar system.

Abstract: Embodiments of the invention are directed toward attenuation correction of radar data. Atmospheric attenuation is a function of atmospheric water drop size and temperature. A number of different theoretical models are available to mathematically describe the particle drop shape that influences attenuation estimation. Each of these models has proven effective in different scenarios. It can be difficult, however, to predict which theoretical model to use. The total differential phase gives an idea of the attenuation, but it depends on the model. Moreover, the total attenuation along a rain path must be apportioned to different parts of the radar path in order to correct for attenuation along a radar path. Embodiments of this invention allows for a system to apportion the attenuation to different parts of the radar beam. Embodiments of the invention also allow for optimization of a number of different theoretical models for both drop size and temperature.

Abstract: Embodiments provide methods, systems, and/or devices that can provide measurements of the inherent reflectivity distribution from different look angles using N radar nodes. Doppler weather radars generally operate with very good spatial resolution in range and poor cross range resolution at farther ranges. Embodiments provide methodologies to retrieve higher resolution reflectivity data from a network of radars. In a networked radar environment, each radar may observe a common reflectivity distribution with different spreading function. The principle that the underlying reflectivity distribution should remain identical for all the nodes may be used to solve the inverse problem to determine intrinsic reflectivities.

Abstract: Embodiments of the invention are directed to improving the sensitivity in polarimetric radar data. In particular, embodiments of the invention improve the sensitivity of such systems with improved post processing techniques. The sensitivity can be improved by using the co-polar elements (off diagonal elements) of the covariance matrix in power and/or reflectivity determinations. This can not only improve the sensitivity but may also enhance identification and improve quantitative estimates of precipitation.

Abstract: Sensitivity is a critical aspect of weather radar systems. Such systems not only detect atmospheric patterns but often need to precisely measure weak precipitation echoes. Embodiments of the invention use pulse compression techniques to increase the sensitivity of weather radar systems. These techniques can include sending two waveforms into a region of interest, where the second waveform is designed based on knowledge about the first waveform. Such systems can enhance the sensitivity of weather radars about 10 dB.

Abstract: Embodiments of the present invention provide a Gaussian adaptive filter for ground clutter filtering and signal parameter estimation for weather radars in the time domain. In some embodiments, the filtering can be applied to dual polarization radar systems. In some embodiments, the clutter component of the signal can be transformed to noise. An interpolation procedure can then be used to recover the transformed part of the weather. A unique filter can be designed to use for both H and V channels for dual-polarization parameter estimation. In addition, the filter can be directly extended for staggered PRT 2/3 sampling scheme.

Abstract: Certain embodiments provide a network waveform system that can include multiple radars disposed at different geographical positions within an environment. The multiple radars may be configured to transmit a network waveform. The network waveform may include multiple radar waveforms. Each radar waveform of the multiple waveforms may be transmitted by a specific radar of the multiple radars. The system can also include a computer system coupled with the multiple radars that can include a processor and a memory. The memory may be configured to store information including data received from the multiple radars, data processed by the processor, and processing code executable by the processor. The processing code may include instructions to receive output data from the multiple radars resulting from the transmitted network waveform instructions to jointly process the output data from the multiple radars to determine a measurement of the environment based on the network waveform.

Abstract: Embodiments of the invention can predict the ground location and intensity of storm cells for a future time using radar reflectivity data. In some embodiments, a Sinc approximation of the general flow equation can be solved to predict the ground location and intensity of a storm cell. In some embodiments, to solve the Sinc approximation the velocity of a storm cell can be estimated using various techniques including solving the flow equation in the frequency domain. The results can provide efficient prediction of storm cell position in nowcasting applications.

Abstract: Embodiments provide methods, systems, and/or devices that can provide measurements of the inherent reflectivity distribution from different look angles using N radar nodes. Doppler weather radars generally operate with very good spatial resolution in range and poor cross range resolution at farther ranges. Embodiments provide methodologies to retrieve higher resolution reflectivity data from a network of radars. In a networked radar environment, each radar may observe a common reflectivity distribution with different spreading function. The principle that the underlying reflectivity distribution should remain identical for all the nodes may be used to solve the inverse problem to determine intrinsic reflectivities.

Abstract: Sensitivity is a critical aspect of weather radar systems. Such systems not only detect atmospheric patterns but often need to precisely measure weak precipitation echoes. Embodiments of the invention use pulse compression techniques to increase the sensitivity of weather radar systems. These techniques can include sending two waveforms into a region of interest, where the second waveform is designed based on knowledge about the first waveform. Such systems can enhance the sensitivity of weather radars about 10 dB.

Abstract: Systems and methods are provided for adaptively estimating the specific differential phase (Kdp) from dual-polarization radar data in the complex domain. Some embodiments adapt for wrapped differential propagation phases by estimating the specific differential phase in the complex domain. Some embodiments adapt for measurement fluctuations and/or spatial scale in making such estimations. Some embodiments also provide for determining the presence of storms cells using the dispersion of the differential propagation phase shift over a subset of bins.

Abstract: Methods and systems for estimating atmospheric conditions are disclosed according to embodiments of the invention. In one embodiment, a method may include receiving reflective atmospheric data and solving a flow equation for motion coefficients using the reflective atmospheric data. Future atmospheric conditions can be estimated using the motion coefficients and the reflective atmospheric data. In another embodiment of the invention, the flow equation is solved in the frequency domain. Various linear regression tools may be used to solve for the coefficients. In another embodiment of the system, a radar system is disclosed that predicts future atmospheric conditions by solving the spectral flow equation.

Abstract: Embodiments of the present invention provide a Gaussian adaptive filter for ground clutter filtering and signal parameter estimation for weather radars in the time domain. In some embodiments, the filtering can be applied to dual polarization radar systems. In some embodiments, the clutter component of the signal can be transformed to noise. An interpolation procedure can then be used to recover the transformed part of the weather. A unique filter can be designed to use for both H and V channels for dual-polarization parameter estimation. In addition, the filter can be directly extended for staggered PRT 2/3 sampling scheme.

Abstract: Certain embodiments provide a network waveform system that can include multiple radars disposed at different geographical positions within an environment. The multiple radars may be configured to transmit a network waveform. The network waveform may include multiple radar waveforms. Each radar waveform of the multiple waveforms may be transmitted by a specific radar of the multiple radars. The system can also include a computer system coupled with the multiple radars that can include a processor and a memory. The memory may be configured to store information including data received from the multiple radars, data processed by the processor, and processing code executable by the processor. The processing code may include instructions to receive output data from the multiple radars resulting from the transmitted network waveform instructions to jointly process the output data from the multiple radars to determine a measurement of the environment based on the network waveform.

Abstract: Methods and systems are disclosed for investigating a region of interest with a radar. A radar signal is propagated to the region of interest. Sampled time-domain radar data scattered within the region of interest are collected. A likelihood function is calculated with the sampled time-domain data within a parametric model of the region of interest for a defined set of parameters. The set of parameters in varied to find an extremum of the likelihood function.