What Signal Processing does

Signal Processing, Inc. (SPI) is an 11-employee (8 PhDs) privately held research and development firm founded in April 2006 and headquartered in Rockville, Maryland. The company develops proprietary machine learning, pattern recognition, and signal processing algorithms across five core capability areas: speech processing (e.g., VSep blind source separation, Spatial-Sep beamforming, dual-microphone speech enhancement achieving SNR improvement from -20 dB to +22 dB, GMM-based Speaker-ID, HMM-based SpeechReg), image and video processing (image denoising outperforming CBM3D, super-resolution for hyperspectral imagery, Kernel-RX anomaly detection, MRCD change detection, video summarization achieving 52x compression, active 3D multi-pixel target tracking, matrix completion at 99.9% missing data), chemical and biological agent detection (CAC-CET classification and concentration estimation, Fluctuation Enhanced Sensing hardware, remote standoff and GC-IMS tools), fault diagnostics and prognostics (cloud-based FDP-BS, adaptive bearing prognostics with online learning, wireless sensor nodes), and multimodal biometrics (Multi-Bio fingerprint plus voiceprint fusion at 1% FRR / 0.2% FAR).

SPI's business model is anchored in U.S. government R&D contracting, with named customers including NASA, the Navy, Army, Air Force, DARPA, MDA, DOE, NIST, and NSF. Revenue is generated primarily through professional services (feasibility studies, consulting, custom algorithm and software development) and licensing of proprietary technology, supplemented by R&D partnerships with defense primes (Lockheed Martin, General Electric, BAE Systems, SAIC, Raytheon) and academic institutions (Johns Hopkins, Carnegie Mellon, Virginia Tech as core collaborators, plus a broader network of partner universities). The firm has filed 12+ invention disclosures and holds 3 patents (2 granted), and extends its technology into consumer and developer markets through a free Good Hearing hearing aid app on iOS/Android and a GitHub Repository Recommendation Chrome extension, though commercial revenue from these products is not disclosed and the company remains fundamentally a small, government-focused R&D boutique.

Name

Signal Processing

Legal name

Signal Processing, Inc.

Website

https://signalpro.net

Company type

Private

Founded year

2006

Operating status

Operating

Headcount range

11–50 employees

Short description

Signal Processing, Inc. (SPI) is an 11-employee Rockville, MD R&D boutique developing proprietary machine learning and signal processing algorithms in speech, image/video, chemical detection, fault diagnostics, and biometrics, primarily serving U.S. government defense and research agencies.

Ownership category

akta.pro rank

Product category

Signal Processing Software

NAICS

Scientific Research and Development Services (5417), Instruments and Related Products Manufacturing for Measuring, Displaying, and Controlling Industrial Process Variables (334513)

SIC

Services-Testing Laboratories (8734)

akta.pro primary industry

Video Analytics & AI Security Solutions Integration (LPR, Facial, Behavior) (BPAKAGAK)

Keywords

• Signal processing software
• Machine learning algorithms
• Pattern recognition systems
• Fault diagnostics software
• Chemical agent detection

Headquarters

HQ city

Rockville

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Operations, Marketing or Sales

Revenue model

1. Government Research Contracts: SPI performs R&D and provides services to U.S. government agencies including Navy, Army, Air Force, DARPA, MDA, DOE, NIST, NSF, ONR, ARO, AFOSR, and others. This is the primary revenue driver.
2. Product Licensing and Royalties: SPI develops proprietary algorithms and software that are licensed to government and commercial customers. The company performs R&D leading to product development and licensing arrangements.
3. Consulting Services: SPI offers feasibility studies, consulting services, custom made solutions and software, and algorithm development for challenging pattern recognition problems.
4. Consumer Application (Good Hearing): Good Hearing app is offered free to download on iOS and Android app stores, likely serving as a consumer-facing product demonstrating SPI's sound processing capabilities.

Go-to-market motion1 record

Distribution channels4 records

Marketing channels3 records

Core offering

Signal Processing, Inc. (SPI) performs research and development leading to product development, licensing, and commercial relationships in signal processing, machine learning, and pattern recognition. The company develops proprietary algorithms and software for speech processing, image/video processing, chemical and biological agent detection, fault diagnostics and prognostics, and multimodal biometrics, delivering them via R&D contracts, consulting, custom solutions, and technology licensing to U.S. government agencies and commercial clients.

Product overview

Signal Processing, Inc. (SPI) is a research and development firm founded in April 2006 with 11 employees (8 with PhDs) offering proprietary machine learning and pattern recognition software and consulting services for government and commercial markets. The product portfolio centers on core signal processing capabilities in four main areas: (1) Speech Processing tools including VSep, Adaptive-VSep, Spatial-Sep, Speaker-ID, SpeechReg, and Dual-Mic Speech Enhancement for voice separation, speaker identification, and speech recognition in noisy environments; (2) Image/Video Processing including Image Denoising, Super-Resolution, Pan Sharpening, Change Detection, Anomaly Detection (Kernel-RX), Target Detection (H-ISAC), Pixel Target Tracking, Video Summarization (VSR), and Matrix Completion; (3) Chemical Detection including CAC-CET for classification/concentration estimation, FES Chemical Detection using Fluctuation Enhanced Sensing, Remote Standoff Detection, and GC-IMS enhancement; (4) Fault Diagnostics and Prognostics including cloud-based FDP-BS, FDP Prototype with wireless sensors, Adaptive Bearing Prognostics, and Multi-thread Multi-core Processing Architecture. The company also offers Good Hearing (consumer hearing aid app) and GitHub Repository Recommendation (developer tool) as consumer-facing sub-brands. All products are delivered as software tools, consulting services, or custom solutions rather than a unified platform.

Differentiator

Problem solved

Functional benefit

Brands

• Good Hearing: High Definition Hearing Aid Application with automatic ambient noise removal, remote voice mode based on HDR algorithm, strong sound amplification, independent volume adjustment for left and right ear, and automatic positive feedback control.
• GitHub Repo Rec

Products and services

• Speech Processing System A suite of voice processing tools including VSep (blind source separation), Adaptive-VSep (online learning), Spatial-Sep (beamforming with interference rejection), Speaker-ID (GMM-based speaker identification), and SpeechReg (HMM-based speech recognition) for separating, identifying, and recognizing voices in noisy multi-speaker environments.
• Dual-Mic Speech Enhancement Speech enhancement algorithm using two microphones with a novel frequency-domain adaptive method, achieving SNR improvement from -20 dB to +22 dB in extremely noisy environments including battlefield conditions.
• Speech Separation for Underdetermined Scenario Near real-time speech separation system for scenarios where the number of speakers exceeds the number of microphones, leveraging sparsity in speech to separate multiple simultaneous speakers.
• Multi-thread Multi-core Processing Architecture Processing architecture for Intel multi-core PCs enabling real-time processing of multiple speaker continuous conversation transcription with 11 microphones at 16kHz sampling.
• Multi-Bio Multimodal Biometric System Personal identification system combining fingerprint and voiceprint biometrics with low-cost sensors, achieving 1% False Rejection Rate at 0.2% False Acceptance Rate for executives, military personnel, and users protecting valuable information.
• Image Denoising Image denoising algorithm that outperforms state-of-the-art CBM3D for real and hyperspectral images, handling real-world noisy photos with unknown and varying noise levels.
• Super-Resolution Algorithm for Hyperspectral Images Algorithm fusing high-resolution color images with low-resolution hyperspectral images (AVIRIS data with 213 bands) to produce high-resolution hyperspectral output.
• Pan Sharpening of Multispectral Images Pan sharpening method preserving color consistency to minimize false alarms in change detection and anomaly detection applications.
• Target Detection (H-ISAC) Hybrid In-Scene Atmospheric Compensation method for hyperspectral target detection that automatically adapts laboratory target signatures to outdoor environments.
• Anomaly Detection (Kernel-RX) Kernel-RX algorithm for hyperspectral anomaly detection via nonlinear mapping to high-dimensional feature space, with CKRX fast approximation variant for large-scale applications.
• Change Detection (MRCD) Change detection using SAR and hyperspectral images with MRCD framework handling illumination change, seasonal change, parallax, and occlusion.
• Active 3D Multiple Target Tracking (Pixel Target Tracking) Pixel size target tracking using extended Kalman filter (EKF) trackers, handling multiple targets, partial observations, missing pixels, false alarms, and automatic camera coordination.
• Multiple Target Tracking (MTT) Multi-target tracking system for surveillance using Kalman filter and IMM filter for maneuvering and non-maneuvering targets, with logic-based track initiation and Munkres algorithm for data association.
• Joint Sensor Registration, Data Association, and Tracking Joint algorithm for multi-sensor multi-target tracking developed under MDA support, handling 8 closely distributed targets with crossing trajectories.
• OTHR Object Detection and Tracking Over-the-Horizon Radar object detection and tracking for ships and low-flying targets such as cruise missiles, handling non-Gaussian non-stationary clutter and maneuvering targets using IMM filter.
• Micro-Doppler Target Identification Algorithms exploiting micro-Doppler features for differentiating missiles from decoys, developed under ONR and MDA support.
• VSR Video Summarization Event-based video summarization tool separating event and non-event segments in real-time, compressing 14-minute videos to 16 seconds (52x) with robust handling of illumination changes, shadows, and multiple objects.
• Matrix Completion for Missing Pixels Reconstruction Novel matrix completion algorithms for reconstructing missing pixels in electro-optical images, achieving excellent reconstruction even at 99.9% missing data with PSNR scores above 25 dB.
• CAC-CET Chemical Agent Classification and Concentration Estimation Modular software tool for classifying and estimating concentrations of chemical agents from nano-sensor outputs, FTIR spectra, and Taguchi sensors, independent of Matlab or Labview.
• Remote Standoff Chemical Detection User-friendly software for Army analyzing data from remote standoff multispectral sensors to detect chemical clouds more accurately than state-of-the-art algorithms.
• GC-IMS Chemical Concentration Estimation Software tool enhancing detection performance in portable Army GC-IMS (Gas Chromatography Ion Mobility Analyzer) for chemical agent detection and concentration estimation.
• FES Chemical Detection (Fluctuation Enhanced Sensing) Hardware portable chemical analyzer with 4-channel simultaneous sensor data collection using Fluctuation Enhanced Sensing principle for chemical and biological agent detection.
• FDP-BS Cloud-Based Fault Diagnostics and Prognostics Cloud-based health monitoring software for rotating machinery, accessible from anywhere via internet-capable devices without software installation or upgrades required.
• FDP Prototype with Adaptive Bearing Prognostics Health monitoring software for rotating machinery using wireless sensors, with health index computation, remaining useful life prediction, and adaptive on-line learning capability without historical data requirement.
• Wireless Sensor Nodes for Machine Diagnostics Custom-made and Zigbee-based wireless sensor nodes for machine diagnostics, with long-range custom nodes and short-range Zigbee mesh network options.
• High Performance Data Compression (PJ) Novel algorithm for both lossy and lossless data compression outperforming JPEG, JPEG-2000, 7z, and Gzip in compression ratio, tested on NIST wind tunnel data.
• Good Hearing Mobile Application
• GitHub Repository Recommendation Chrome Extension

Quantifiable outcome

• 1% False Rejection Rate at 0.2% False Acceptance Rate in multimodal biometric identification
• +4 more outcomes

Named customers9 records

Segments2 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

AI capability22 records

Feature21 records

Partnerships

18 partnerships are on record, tiered core and minor.

• Johns Hopkins UniversitycoreStrategic or Co-development PartnerSPI works with consultants and subcontractors at Johns Hopkins University who form an integral part of the company. Collaboration focuses on algorithm design and implementation in signal processing, pattern recognition, and machine learning.
• Carnegie Mellon UniversitycoreStrategic or Co-development PartnerSPI works with consultants from Carnegie Mellon University as part of its extended team, contributing to research in speech processing, pattern recognition, and diagnostics.
• Virginia TechcoreStrategic or Co-development PartnerSPI collaborates with Virginia Tech researchers who are integrated into the company's project work, particularly in signal/image processing and pattern recognition.
• West Virginia UniversityminorStrategic or Co-development PartnerClose collaboration with university researchers for joint research and development in signal processing and pattern recognition.
• University of Maryland at College ParkminorStrategic or Co-development PartnerCollaboration in research and development activities, contributing expertise in pattern recognition and signal processing.
• University of Missouri at ColumbiaminorStrategic or Co-development PartnerUniversity partnership for collaborative R&D in signal processing and related technical areas.
• University of DelawareminorStrategic or Co-development PartnerAcademic collaboration contributing to the company's research capabilities in signal processing.
• Arizona State UniversityminorStrategic or Co-development PartnerUniversity collaboration in pattern recognition and signal processing research.
• University of Texas at ArlingtonminorStrategic or Co-development PartnerUniversity partnership for collaborative R&D in signal processing and related technical areas.
• UT Pan AmericanminorStrategic or Co-development PartnerAcademic collaboration contributing to the company's research capabilities.
• University of Colorado at BoulderminorStrategic or Co-development PartnerUniversity collaboration in research and development activities.
• University of CalgaryminorStrategic or Co-development PartnerAcademic partnership contributing to signal processing research capabilities.
• University of TennesseeminorStrategic or Co-development PartnerUniversity collaboration for joint research in signal processing and related disciplines.
• Lockheed MartinminorStrategic or Co-development PartnerClose collaboration on defense-related R&D projects involving signal processing and pattern recognition algorithms.
• General ElectricminorStrategic or Co-development PartnerCollaboration on fault diagnostics and prognostics research, particularly for industrial and rotating machinery applications.
• BAE SystemsminorStrategic or Co-development PartnerCollaboration on defense technology development involving signal processing and related applications.
• SAICminorStrategic or Co-development PartnerPartnership on government defense and security-related R&D projects.
• RaytheonminorStrategic or Co-development PartnerCollaboration on defense and security technology development involving signal processing and pattern recognition.

Scale indicators3 records

Recent moves6 records

Expansion highlights5 records

Direct peers

• Leidos: Leidos provides federal R&D, sensor processing, and analytics services, including significant work in signal processing, image exploitation, and CBRNE detection for the DoD, making it a directly comparable government R&D services peer.
• Peraton: Peraton is a government services company focused on intelligence, defense, and homeland security mission work, including signal and image processing R&D, and competes with SPI for similar federal R&D contract vehicles.
• Booz Allen Hamilton: Booz Allen Hamilton is a federal consulting and engineering services firm with deep DoD/IC relationships in AI, signal processing, and mission analytics, comparable to SPI as a government R&D and engineering services competitor.
• CACI International: CACI delivers government IT, signals intelligence, and electronic warfare R&D services across the DoD and intelligence community, competing with SPI for federal signal processing and sensor analytics task orders.
• SAIC: SAIC is a large government IT and scientific R&D services contractor that directly competes with SPI for federal signal processing, intelligence, and defense analytics contracts across DoD, intelligence community, and civilian agencies.

Broad incumbents

• BAE Systems: BAE Systems is a global defense prime with substantial work in electronic systems, signal intelligence, and sensor processing, operating both as a competitor to and a potential partner with SPI on defense R&D programs.
• Lockheed Martin: Lockheed Martin operates in defense aerospace and mission systems with extensive internal signal processing and machine learning R&D, both competing with and acting as a prime contractor that could pull in SPI as a subcontractor.
• Raytheon: Raytheon (now part of RTX) is a major defense prime that absorbs signal processing and sensor analytics R&D across airborne radar, electronic warfare, and missile programs, often partnering with or competing against small R&D boutiques like SPI.

Emerging players

• HRL Laboratories: HRL Laboratories is a small, research-intensive lab (formerly Hughes Research) specializing in signal processing, sensors, and AI, and is a like-sized R&D boutique competing for similar defense and intelligence community research dollars.
• SRI International: SRI International is a non-profit R&D institute performing contract research in signal processing, AI, and sensors for government clients, comparable to SPI as a federally funded R&D organization with similar technology focus areas.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat5 records

Key risks6 records

Key highlights6 records

Customer concentration

• LinkedInlinkedin.com/company/signal-processing-inc-

Revenue estimate

Valuation estimate

Number of profiles

Profiles1 record

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Signal Processing