Abstract: A linear detection method for determining correlation values associated with an estimated Pulse Repetition Interval (PRI) executed by a linear detection module of a correlation mask disposed on a digital signal processor is provided comprising: determining a correlation spread associated with a vector of Times-of-Arrival (TOA) data; determining a delta spread associated with the correlation spread; determining a first/next estimated PRI associated with the vector of TOA data; determining a first/next estimated PRI vector based on the first/next estimated PRI; determining a delta vector based on the first/next estimated PRI vector; determining a correlation weights vector based on the delta vector; determining a first/next correlation value based on the correlation weights vector; and in response to there being no additional PRIs to estimate, searching the correlation values for a highest correlation.

Abstract: Algorithmic approaches that can be implemented in software/firmware/hardware that filters out stable PRI patterns detected within a system that is prosecuting against radar based transmissions are disclosed. The algorithms allow downstream computing assets to concentrate their limited resources on the more complex emitter PRI pattern types. Thus, a portion (e.g., stable signals) of the pulse deinterleave and PRI identification problem is solved without requiring the more computationally expensive processing. The disclosed algorithms can be employed, for example, in electronic support measures (ESM) systems, electronic intelligence (ELINT) systems, and/or electronic countermeasures (ECM) systems. The algorithms employ linear detection, linear regression, or a combination of linear detection and linear regression, thereby providing a “dual voting” scheme that decreases the occurrence of false positives.

Abstract: An algorithmic approaches that can be implemented in software/firmware/hardware that filters out stable PRI patterns detected within a system that is prosecuting against radar based transmissions are disclosed. The algorithms allow downstream computing assets to concentrate their limited resources on the more complex emitter PRI pattern types. Thus, a portion (e.g., stable signals) of the pulse deinterleave and PRI identification problem is solved without requiring the more computationally expensive processing. The disclosed algorithms can be employed, for example, in electronic support measures (ESM) systems, electronic intelligence (ELINT) systems, and/or a electronic countermeasures (ECM) systems. The algorithms employ linear detection, linear regression, or a combination of linear detection and linear regression, thereby providing a “dual voting” scheme that decreases the occurrence of false positives.

Abstract: An algorithmic approaches that can be implemented in software/firmware/hardware that filters out stable PRI patterns detected within a system that is prosecuting against radar based transmissions are disclosed. The algorithms allow downstream computing assets to concentrate their limited resources on the more complex emitter PRI pattern types. Thus, a portion (e.g., stable signals) of the pulse deinterleave and PRI identification problem is solved without requiring the more computationally expensive processing. The disclosed algorithms can be employed, for example, in electronic support measures (ESM) systems, electronic intelligence (ELINT) systems, and/or a electronic countermeasures (ECM) systems. The algorithms employ linear detection, linear regression, or a combination of linear detection and linear regression, thereby providing a “dual voting” scheme that decreases the occurrence of false positives.

Abstract: A method is provided to prompt an engineer to more completely specify the product desired so as to minimize misinterpretation and misunderstanding leading to improper design and improper product outcome downstream. In one embodiment, the individual generating the specification is instructed to consider a series of questions that relate to the particular function and its behavior, as well as the end performance characteristics of the final product, also including questions relating to cost, priority of the requirement itself and any internal integration and test functions. In addition to the questions, categories of requirements are also utilized depending on the type of specification to be generated. The result of considering a pre-selected set of questions coupled with a pre-selected set of categories is that a more complete and better understanding of the project from both the product developer and the product specified can be obtained.

Abstract: A linear detection method for determining correlation values associated with an estimated Pulse Repetition Interval (PRI) executed by a linear detection module of a correlation mask disposed on a digital signal processor is provided comprising: determining a correlation spread associated with a vector of Times-of-Arrival (TOA) data; determining a delta spread associated with the correlation spread; determining a first/next estimated PRI associated with the vector of TOA data; determining a first/next estimated PRI vector based on the first/next estimated PRI; determining a delta vector based on the first/next estimated PRI vector; determining a correlation weights vector based on the delta vector; determining a first/next correlation value based on the correlation weights vector; and in response to there being no additional PRIs to estimate, searching the correlation values for a highest correlation.