DESC:
FORM – 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
(SEE SECTION 10, RULE 13)

“SYSTEM AND METHOD FOR OPTIMIZING RANGE SPREAD EFFECT ON VOLUMETRIC RETURNS FOR WEATHER RADARS”

BHARAT ELECTRONICS LIMITED
WITH ADDRESS: OUTER RING ROAD, NAGAVARA, BANGALORE 560045, KARNATAKA, INDIA

THE FOLLOWING SPECIFICATION DESCRIBES THE INVENTION.

TECHNICAL FIELD OF THE INVENTION
The present disclosure relates in general to radar signal processing, and more particularly, relates to a system or method for identifying the range spread for volume returns and estimation of weather parameters.
BACKGROUND OF THE INVENTION
Generally, weather radars provide valuable information on various weather phenomenon such as rain, hail, storm, etc. based on reflected power returns from volumetric returns. Conventionally, weather radars transmit a plurality of types of transmitted waves and analyze the reflected waves of the transmitted waves to observe the meteorological conditions. The weather radar compresses the time axis of the signal based on the reception of the reflected wave of the short-pulse and long pulse transmitted waves. Thereafter, the weather radar measures the distance of the reflected object.
Further, conventional radar devices utilize pulse compression in order to improve a signal to noise (SNR) ratio or a distance resolution of a reception signal. In the existing systems, a radar pulse compression repair (RPCR) is implemented in operating upon an output of a matched filter enables RPCR to be employed as a post-processing stage in the systems (e.g., weather radar) where it is not feasible to replace the existing pulse compression apparatus. In addition, RPCR can also be selectively employed when it is possible that large targets are present that may be masking smaller targets, thereby keeping computational complexity to a minimum.
However, due to finite length of received signal, undesirable effect in the range spectrum is observed which affects weather prediction capabilities of weather radar. Moreover, virtual image obtained upon performing compression of long-pulse reflected wave reflected by the object that is existing in the short-distance region is distorted. In fact, the compressed virtual image may appear in the long-distance region. In other words, range side lobes may occur which results in a false image. To that effect, the weather conditions may be discontinuous. Further, different spectrum of the volume returns is distorted at the edges due to spread in range of the returned signal for the modulated waveform transmission in the weather radar. In addition, effective noise floor of the nearby range cell is also increased, thus resulting in inaccurate weather parameters estimation.
Therefore, there is a need for techniques for addressing the above-mentioned problems, in addition to providing other technical advantages.
OBJECTIVE OF THE INVENTION
The main objective of the present invention is to provide a system or method that can identify the range spread for volume returns and mitigate its effects and improve the weather parameters estimation.
SUMMARY OF THE INVENTION
The main objective of the present invention is to provide a system or method that can identify the range spread for volume returns and mitigate its effects and improve the weather parameters estimation.
In accordance with an exemplary implementation of the present invention the system for optimizing range spread effect on volumetric returns for weather Radars, the system comprising a data extractor module adapted to receive real time input data; and a signal quality qualifier module adapted to calculate the quality index of the input data as weather returns wherein quality index of input data helps in isolating range spread from actual weather returns.
In accordance with an exemplary implementation of the present invention, the signal quality qualifier module adapted to calculate the quality index of the input data using a zeroth moment of the input data, a first moment of the input data and a ratio between the first moment of the input data to the zeroth moment of the input data. In another implementation of the present invention the signal quality qualifier module adapted to calculate the quality index of the input data using pulse pair processing.
In accordance with an exemplary implementation of the present invention the normalized Integrator 1 module adapted to receive zeroth moment of the input data from signal quality qualifier module; a normalized Integrator 2 module adapted to receive the ratio between the first moment of the input data to the zeroth moment of the input data from signal quality qualifier module; a signal index calculator (SIC) module adapted to calculate the value of signal index using output of both the normalized integrator1 and the normalized integrator 2; and a spurious removal module adapted to compare the signal index value of each range cell with user selected margin wherein if the calculated value of the spurious removal module is more than the reflected value then the signal quality flag for metrological returns is set for the corresponding range cell.
In accordance with an exemplary implementation of the present invention the spurious removal module adapted to generate spurious flag for each range cell based on signal index value of signal index calculator (SIC) module to remove non-metrological returns based on the volume coverage of returns.
In accordance with an exemplary implementation of the present invention isolating the range spread of weather returns from actual weather return help improving the overall weather estimation by at least 5%.
In accordance with an exemplary implementation of the present invention the spurious removal module adapted to remove the effect of non-metrological returns by at least 40dB.
In accordance with an exemplary implementation of the present invention the signal quality qualifier module, normalized integrators, signal index calculator, signal quality qualifier and spurious removal module are implemented in parallel architecture, providing the delay of less than 4 clock cycles of operational frequency.
In accordance with an exemplary implementation of the present invention the a method for optimizing range spread effect on volumetric returns for weather the method comprising: receiving real time input data from a data extractor module; and calculating the quality index of the input data by a signal quality qualifier module, to determine in isolating range spread from actual weather returns.

BRIEF DESCRIPTION OF ACCOMPANYING DRAWINGS
The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and modules.
FIG. 1 illustrates a simplified block diagram representation of a system for optimizing range spread effect on volumetric returns, in accordance with an embodiment of the present disclosure;
FIG. 2 illustrates a simplified block diagram representation of the system including one or more processing components, in accordance with an embodiment of the present disclosure;
FIG. 3 is an example representation of a state diagram, in accordance with an embodiment of the present disclosure; and
FIGS. 4A and 4B, represent a normalized reflectivity of simulated weather returns and corresponding calculated signal index value, in accordance with an embodiment of the present disclosure.
It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative methods embodying the principles of the present disclosure. Similarly, it will be appreciated that any flow charts, flow diagrams, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computer or processor, whether or not such computer or processor is explicitly shown.
DETAILED DESCRIPTION
In the following description, for the purpose of explanation, specific details are set forth in order to provide an understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced without these details. One skilled in the art will recognize that embodiments of the present disclosure, some of which are described below, may be incorporated into several systems.
The terms and words used in the following description and claims are not limited to the bibliographical meanings but are merely used by the inventor to enable a clear and consistent understanding of the invention. It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.
References in the specification to “one embodiment” or “an embodiment” mean that a particular feature, structure, characteristic, or function described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
It should be noted that the description merely illustrates the principles of the present invention. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present invention. Furthermore, all examples recited herein are principally intended expressly to be only for explanatory purposes to help the reader in understanding the principles of the invention and the concepts contributed by the inventor to furthering the art and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to encompass equivalents thereof.
In an embodiment of the present invention, a unique system and method for removing range spread of volumetric returns for weather radars in a scenario where modulated waveforms are used for transmission. The present system calculates the quality index of the input data using zeroth and first moment of the input data and then utilizes this value to calculate signal index value. Further, the weather return is classified as actual returns or returns due to spread based on the signal index value.
In the present invention, range side lobes are restricted to participate in calculation of base products for weather radars to improve size and shape estimation of weather particles.
In the present invention, an effective architecture to eliminate isolated detection from non-metrological returns for better weather prediction is provided.
In the present invention, the calculation latency is reduced in order to improve the rate at which prediction are done.
The present invention discloses a system designed to optimize the accuracy of volumetric returns for weather radars by effectively isolating range spread effects from actual weather returns. The system consists of a data extractor module to process real-time input data and a signal quality qualifier module responsible for calculating the quality index of the input data, aiding in the identification of weather returns. This quality index is determined using various parameters, including zeroth and first moments of the input data and a ratio between them, as well as through pulse pair processing. Additional modules, such as normalized integrators, a signal index calculator, and a spurious removal module, further refine the analysis.
Furthermore, the method outlined allows for the optimization of range spread effects by utilizing the quality index calculation to distinguish between weather and non-weather returns, offering a comprehensive solution for enhancing weather radar performance.
The weather estimation system features modules that isolate weather return ranges, significantly enhancing overall estimation accuracy. Isolating the range spread of weather returns improves overall weather estimation by a minimum of 5%. It includes a spurious removal module that effectively eliminates non-meteorological returns by at least 40dB. The system's parallel architecture implementation ensures operational efficiency, with essential modules functioning with a delay of less than four clock cycles at the operational frequency. This configuration optimizes signal processing speed and filtering capabilities, enabling more precise weather forecasting.
Various embodiments of the present disclosure are further described with reference to FIG. 1 to FIGS. 4A-4B.
FIG. 1 illustrates a simplified block diagram representation of a system for optimizing range spread effect on volumetric returns for weather radars, in accordance with an embodiment of the present disclosure. Typically, weather radars provide valuable information on various weather phenomena such as rain, hail, storm, etc. based on reflected power returns from volumetric returns. For timely warnings and more accurate measurements for precipitation and wind field, an efficient weather radar signal processor (SP) is critical. The SP should be adaptable and should be capable of estimating base products with better accuracy.
The system includes integrated circuits (ICs) to support local area network (LAN) communication, memory for on-board storage, clock distributor IC to distribute the clock required by different ICs, flash to store the code for programmable device and programmable device to implement the different processing blocks of proposed method.
Specifically, the system includes a first local area network (1) (represented as ‘LAN1’) to receive real time I, Q data from external system based on data interrupt signal. It is to be noted that the required configuration parameters for the system is also received from the first LAN (1). The system further includes a programmable device (2). The programmable device (2) is used to implement all the processing block (as shown in FIG. 2) of the system. Further, the system includes a memory (3). The memory (3) is configured for Ping-Pong mode and is used to store the data for one coherent interval of radar. Furthermore, a second local area network (4) (represented as LAN2) is used to send the Spurious Flag, Signal Qualifier flag & Range Cell information as part of flag report, and flash (5) is used to store the permanent executable file for the programmable device. The system includes clock distributor (6) to distribute the external clock or programmable device clock to different components of the system.
FIG. 2 illustrates a simplified block diagram representation of the system including one or more processing components, in accordance with an embodiment of the present disclosure. As shown in FIG. 2, the system receives real-time input from the external system (not shown in figures). The real-time input includes real time I, Q data, range cell data & configuration parameters. Specifically, the system includes a data extractor module (7) for receiving the real-time inputs. Thereafter, the data extractor module (7) distributes the real-time I, Q data to a signal quality qualifier (9), range cell value to a report generator (15) and configuration parameters to a configuration parameter extractor (14).
The signal quality qualifier module (9) calculates a quality index of the real-time input data using zeroth and first moment of the real-time input data using pulse pair processing. Further, computing the quality index using the zeroth and first moment of the real-time input data is represented in the following equations.
R0= (?¦I^2 +Q^2)/N…………Eq.1

R1= (?¦(I_n+jQ_n ) (I_(n-1)+jQ_(n-1) ))/N………………Eq.2

SQR=abs(R1)/R0………………Eq.3

Wherein,
R0 and R1 is the zeroth and first moment respectively,
SQR is signal quality ratio, and the value of SQR will be within the range of 0 to 1, where 1 being the case for ideal volumetric spread,
N is the total number of pulses, and
In and Qn are the data for nth pulse.
The value of SQR will be within 0 to 1, 1 being the case for ideal volumetric spread.
The system includes a first normalized integrator module (10) (represented as ‘Normalizer Integrator 1’) takes zeroth moment data from signal quality qualifier module (9) and calculates the normalized moving average of the zeroth moment using optimum window size of moving average. The output of the first normalized integrator module (10) will be within 0 to 1, where 1 being the case for maximum return strength.

Further, the system includes a second normalized integrator module (11) (represented as Normalized Integrator 2) takes the SQR data from signal quality qualifier module (9) and calculate the normalized moving average of the signal quality ratio using same window size of moving average similar to the first normalized integrator module (10). The output of the second normalized integrator module (11) may be within 0 to 1, where 1 being the case for ideal volumetric spread.
A signal index calculator (SIC) module (12) of the system calculates the value of signal index using output of the first and second normalized integrator modules (10, 11). In particular, the SIC module (12) multiplies the normalized zeroth moment data with normalized SQR data to obtain the signal index (SI) value. In an embodiment, the value of signal index may be between 0 to 1, where 1 being the case for ideal volumetric spread.
The system includes a spurious removal module (13). The spurious removal module (13) compares the signal index value of each range cell with user selected margin (‘T’). Further, the SIC module (13) checks if the calculated value is more than reflected value and sets the signal quality (SQ) flag for metrological returns for the corresponding range cell. In particular, the spurious removal module (13) generates a spurious flag for each range cell based on signal index value of the SIC module (12). The spurious flag is only intended to remove non-metrological returns based on the volume coverage of returns. The spurious removal module (13) compares the signal index value of the neighboring cells in range & azimuth and if the difference is more than predefined value (C) then the return from the current range cell is set as non-metrological return and corresponding flag (Spurious flag). The spurious removal module (13) performs the comparison using the following equation.
?abs(SI?_t-?SI?_(t-1))>C and ?abs(SI?_Ø-?SI?_(Ø-1))>C……… Eq.4

Wherein,
SIt and SIt-1 are the signal index value of current range cell and previous range cell sample, respectively,
SIØ and SIØ-1 are the Signal Index value of the current azimuth and previous azimuth sample, respectively, and
C is the user input value for the required difference level comparison.

As shown, the system includes a flag report generator module (15). The flag report generator module (15) generates a flag report based on the flag received from the signal quality qualifier module (9), the spurious removal module (13), and the data extractor module (7). In addition, the flag report generator module (15) delays the range cell value received from data extractor module (7) to match the flags (spurious flag and SQ flag) with its associated range cells.
The system further includes a configuration parameter extractor (14). The configuration parameter extractor (14) receives the configuration parameters as input from the data extractor module (7) and transmits the configuration parameters to the first and second normalized integrator modules (10, 11). Additionally, the configuration parameter extractor (14) transmits the configuration parameters to the signal quality qualifier module (9) and spurious removal module (13).
Furthermore, in the present invention the system disclosed herein employs a parallel architecture to implement several critical modules, including the Signal Quality Qualifier, Normalized Integrator, Signal Index Calculator, Signal Qualifier, and Spurious Removal module within a Programmable Device. This parallel architecture allows these modules to operate simultaneously, rather than sequentially, which significantly reduces processing time. By processing tasks in parallel, each module can execute its operations concurrently, leading to faster overall performance. Additionally, the architecture ensures that the delay introduced by each module is minimized to less than four clock cycles of the operational frequency. This optimized design not only enhances the system's efficiency but also enables real-time processing of weather data, facilitating timely and accurate weather estimation and forecasting.
FIG. 3 is an example representation of a state diagram, in accordance with an embodiment of the present disclosure. As shown, all the stages in the state diagram are controlled by timing signals. In one scenario, if correct data is not available for a present state, the control is routed to a previous state, or a delay of a threshold time is introduced for the current state.
WORKING EXAMPLES:
FIGS. 4A and 4B, represent a normalized reflectivity of simulated weather returns and corresponding calculated signal index value, in accordance with an embodiment of the present disclosure. In one example, two weather returns of width 900m is simulated at 16.5km and 17.7km, respectively. As shown in FIG. 4A, the value of signal index is close to 1 near the simulated weather returns. Further, the value of signal index is between 1 and 0 near the disturbed area of simulated weather returns. Furthermore, the value of signal index is close to 0 for noise. It is to be noted that with proper selection of user selected margin (‘T’, in this case 0.9), the signal quality flag will be set only for the simulated weather returns region. Thus, it is understood that there is removal of range spread of volumetric returns for weather radars and also non-metrological (spurious) returns are removed.
The foregoing description of the invention has been set merely to illustrate the invention and is not intended to be limiting. Since modifications of the disclosed embodiments incorporating the substance of the invention may occur to person skilled in the art, the invention should be construed to include everything within the scope of the invention.
,CLAIMS:WE CLAIM
1. A system for optimizing range spread effect on volumetric returns for weather Radars, the system comprising:
- a data extractor module (7) adapted to receive real time input data; and
- a signal quality qualifier module (8) adapted to calculate the quality index of the input data as weather returns wherein quality index of input data helps in isolating range spread from actual weather returns.

2. The system as claimed in claim 1, wherein the signal quality qualifier module (8) adapted to calculate the quality index of the input data using a zeroth moment of the input data, a first moment of the input data and a ratio between the first moment of the input data to the zeroth moment of the input data.

3. The system as claimed in claim 1, wherein the signal quality qualifier module (8) adapted to calculate the quality index of the input data using pulse pair processing.

4. The system as claimed in claim 1, further comprises:
- a normalized Integrator 1 module (10) adapted to receive zeroth moment of the input data from signal quality qualifier module (8);
- a normalized Integrator 2 module (11) adapted to receive the ratio between the first moment of the input data to the zeroth moment of the input data from signal quality qualifier module (8);
- a signal index calculator (SIC) module (12) adapted to calculate the value of signal index using output of both the normalized integrator1 and the normalized integrator 2; and
- a spurious removal module (13) adapted to compare the signal index value of each range cell with user selected margin wherein if the calculated value of the spurious removal module is more than the reflected value then the signal quality flag for metrological returns is set for the corresponding range cell.

5. The system as claimed in claim 4, wherein spurious removal module (13) adapted to generate spurious flag for each range cell based on signal index value of signal index calculator (SIC) module to remove non-metrological returns based on the volume coverage of returns.

6. The system as claimed in claim 1, wherein isolating the range spread of weather returns from actual weather return help improving the overall weather estimation by at least 5%.

7. The system as claimed in claim 4, wherein spurious removal module (13) adapted to remove the effect of non-metrological returns by at least 40dB.

8. The system as in claim 4, wherein signal quality qualifier module (8), normalized integrators (10,11), signal index calculator (12), signal quality qualifier (9) and spurious removal module (13) are implemented in parallel architecture, providing the delay of less than four clock cycles of operational frequency.

9. A method for optimizing range spread effect on volumetric returns for weather Radars, the method comprising:
- receiving real time input data from a data extractor module (7); and
- calculating the quality index of the input data by a signal quality qualifier module (8), to determine in isolating range spread from actual weather returns.

Dated this 31st day of March 2023
FOR BHARAT ELECTRONICS LIMITED
(By their Agent)

(D. Manoj Kumar) (IN/PA 2110)
KRISHNA & SAURASTRI ASSOCIATES LLP